Results for “achieved” — Page 21

NASA NTRSDate not supplied

The Nasa Multiscale Analysis Tool: an Enabling Platform for Achieving Vision 2040

Vision 2040 is a community-driven consensus document, written in 2018, aimed at defining the potential 25-year future state required for performing integrated multiscale modeling of materials and systems for future aerospace and aeronautical applications. Nine Vision Key Elements (KEs) were defined along with associated technical gaps. This paper will address current NASA GRC research efforts utilizing the NASA Multiscale Analysis Tool (NASMAT). This paper will specifically focus on NASMAT’s ability to address gaps in three of the nine Vision 2040 KEs: 1) Models and Methods, 2) Multiscale Measurements and Characterization Tools and Methods, and 6) Data, Informatics, and Visualization. NASMAT is a versatile platform for performing computationally efficient multiscale analyses of heterogeneous materials. NASMAT offers the user flexibility to define an arbitrary number of length scales (levels) where a variety of micromechanics theories can be implemented at each level. Micromechanics theories can be selected to balance accuracy and computational efficiency and range from analytical (Mori-Tanaka) to several semi-analytical (method of cells) formulations. NASMAT can also be coupled with external software and used to perform multiscale analyses of more complex structures. The paper will include a recent application of NASMAT to model a complex, three-dimensional woven composite, with a particular emphasis placed on multiscale measurements utilized to enhance the quality of the multiscale analysis. Since typical NASMAT analyses can be completed in on the order of seconds to minutes, a second example will demonstrate NASMAT’s ability to generate large quantities of data useful for sensitivity analysis, uncertainty quantification, or machine learning applications. Current progress on developing multiscale data visualization tools will also be addressed along with the challenges associated with and proposed solutions for sifting through large amounts of data. These examples will demonstrate that NASMAT is an enabling platform for achieving the goals in Vision 2040.

Vision 2040↗

NASA NTRS2024

Achieving High Efficiency in Reduced Order Modeling for Large Scale Polycrystal Plasticity Simulations

Reduced order models for the nonlinear response of heterogeneous microstructures typically require a construction (or training) stage to build the reduced order basis. In this manuscript, an efficient model construction strategy for the eigenstrain homogenization method (EHM) is presented. The proposed strategy relies on a parallel, element-by-element, conjugate gradient solver. Near linear scaling has been achieved with respect to the number of degrees of freedom used to resolve the microstructure. Linear scaling with respect to the number of pre-analyses required to construct the reduced order model (ROM) follows from the EHM formulation. Furthermore, a parallel implementation for fast evaluation of the constructed ROM has been developed using shared memory parallelization. It has been shown that for large microstructures with ≈ 10,000 grains, the total computational cost of evaluating the nonlinear response of a polycrystal could be reduced by approximately an order of magnitude using 32 cores with respect to serial ROM simulation. The present methodology has been verified using an additively manufactured polycrystalline microstructure of a nickel-based superalloy, Inconel 625. The capability of the developed framework to construct a ROM for such large microstructures, as well as the ability of the ROM to predict average and local quantities of interest has been demonstrated.

microscale↗

NASA NTRS2023

An Enabling Platform for Achieving Multiscale Multiphysics Analysis of Multiphase Materials

This paper will address current NASA GRC research efforts utilizing the NASA Multiscale Analysis Tool (NASMAT) which address technical gaps in three of the Vision 2040 key discipline areas. NASMAT is a versatile platform for performing computationally efficient multiscale analyses of heterogeneous materials and is available free through the NASA software catalog. It offers the user flexibility to define an arbitrary number of length scales (levels) where a variety of micromechanics theories can be implemented at each level. Micromechanics theories can be selected to balance accuracy and computational efficiency and range from analytical (Mori-Tanaka) to several semi-analytical (method of cells) formulations. The resulting anisotropic, evolving nonlinear, thermomechanical constitutive model can also be coupled with external software and used to perform multiscale analyses of more complex structures. A recent application to model a complex, three-dimensional woven composite, with a particular emphasis placed on multiscale measurements utilized to enhance the quality of the multiscale analysis will be discussed. Since typical NASMAT analyses can be completed on the order of seconds to minutes, a second example will demonstrate the ability to generate large quantities of data useful for sensitivity analysis, uncertainty quantification, or machine learning applications. Current progress on implementing NASMAT within a multiscale digital thread/digital twin framework will also be addressed. These examples will demonstrate that NASMAT is an enabling platform for achieving the goals in Vision 2040.

Multiscale↗

NASA NTRSDate not supplied

Reliability-Based Damage Tolerance Framework for Achieving Highly Reusable Launch Systems

The United States Space Force and NASA are exploring approaches that enable rapid launch response via highly reusable launch systems. One hindrance to achieving high reusability is the inability to meet damage tolerance requirements. To this end, a framework for applying reliability-based damage tolerance to space structures is presented. The reliability-based approach employs probabilistic distributions of key input variables such as material properties, geometry, loads, inspection probability, and defect characteristics to predict hardware reliability for the planned mission life. The probabilistic variables needed to perform the reliability assessments are defined and recommendations on how to collect the required data are provided. Several example problems illustrate the implementation and execution of this approach.

Leland Shimizu↗

NASA NTRSDate not supplied

Balancing Manufacturability with Performance: Achieving Extrudable, High Thermal Conductivity, and Dielectrically Robust Thermoplastic Composites

Improved thermal management solutions for electrical insulation systems are a priority for increasing efficiency. Although polymeric electrical insulation is ubiquitous, it generally exhibits low thermal conductivities (κ ; 0.1 – 0.3 W/mK). High κ electrical insulation systems are desirable for several reasons including improved heat wicking. Polymer-ceramic composites offer a viable path towards increasing κ of electrical insulation systems. However, processing-induced anisotropic particle orientation can result in prohibitively high concentrations of high κ particles being required to achieve impactful improvements. This work evaluates the effectiveness of a double percolation approach and its impacts on extruded polymer composite insulation κ using polyimide (PI), polyphenylsulfone (PPSU), and hexagonal boron nitride (hBN). Thermoplastic composite blends of PI/PPSU exhibited a 15% improvement in composite κ at comparable loading levels of hBN relative to mono-polymer material systems. On the other hand, PI/PPSU/hBN composites exhibited lower dielectric strengths than either neat polymer/hBN composite. A trade-off between maximizing material κ and resultant processing and dielectric performances may exist when using a double percolation approach for thermoplastic composites.

Witold K. Fuchs↗

NASA NTRS2024

A Method of Compliance for Achieving Target Collision Risk in UTM Operations

This work proposes a method of compliance to ensure that the collision risks among small unmanned aircraft systems meet the target level of safety. This method presents what is needed for a strategic conflict detection service to achieve the target level of safety when conflict between operational intents are not permitted in nominal situations. A volume-based collision risk model is first developed to calculate the UA-to-UA collision risk given any two operational intent volumes. With this collision risk model, a test strategy is then proposed to assess if a strategic conflict detection service can reduce the collision risk and meet the target level of safety. The method also specifies operational data that are required to be collected to verify if requirements on conformance are being met. Additionally, two new requirements are identified and proposed by this method beyond the current standard for strategic conflict detection. In the sensitivity analysis, three main factors contributing to the collision risk are investigated. The analysis shows that buffers should be considered in a strategic conflict detection service when deconflicting operational intents. The results also reveal that the selection of test cases plays an important role in evaluating the strategic conflict detection service, and they should be representative and sufficiently complex in evaluation tests.

Collision Risk↗

NASA NTRSDate not supplied

A Method of Compliance for Achieving Target Collision Risk in UTM Operations

This work proposes a method of compliance to ensure that the collision risks among small unmanned aircraft systems meet the target level of safety. This method presents what is needed for a strategic conflict detection service to achieve the target level of safety when conflict between operational intents are not permitted in nominal situations. A volume-based collision risk model is first developed to calculate the UA-to-UA collision risk given any two operational intent volumes. With this collision risk model, a test strategy is then proposed to assess if a strategic conflict detection service can reduce the collision risk and meet the target level of safety. The method also specifies operational data that are required to be collected to verify if requirements on conformance are being met. Additionally, two new requirements are identified and proposed by this method beyond the current standard for strategic conflict detection. In the sensitivity analysis, three main factors contributing to the collision risk are investigated. The analysis shows that buffers should be considered in a strategic conflict detection service when deconflicting operational intents. The results also reveal that the selection of test cases plays an important role in evaluating the strategic conflict detection service, and they should be representative and sufficiently complex in evaluation tests.

UTM, Method of Compliance, collision risk↗

NASA NTRSDate not supplied

A Method of Compliance for Achieving Target Collision Risk in UTM Operations

This work proposes a method of compliance to ensure that the collision risks among small unmanned aircraft systems meet the target level of safety. This method presents what is needed for a strategic conflict detection service to achieve the target level of safety when conflict between operational intents are not permitted in nominal situations. A volume-based collision risk model is first developed to calculate the UA-to-UA collision risk given any two operational intent volumes. With this collision risk model, a test strategy is then proposed to assess if a strategic conflict detection service can reduce the collision risk and meet the target level of safety. The method also specifies operational data that are required to be collected to verify if requirements on conformance are being met. Additionally, two new requirements are identified and proposed by this method beyond the current standard for strategic conflict detection. In the sensitivity analysis, three main factors contributing to the collision risk are investigated. The analysis shows that buffers should be considered in a strategic conflict detection service when deconflicting operational intents. The results also reveal that the selection of test cases plays an important role in evaluating the strategic conflict detection service, and they should be representative and sufficiently complex in evaluation tests.

UTM↗

NASA NTRSDate not supplied

A Deep Neural Network for Achieving Spectrally Consistent and Seamless Infrared Radiance Measurements Across Geostationary Satellite Domains

The NASA Clouds and the Earth's Radiant Energy System (CERES) project provides the scientific community with observed top-of-atmosphere (TOA) shortwave and longwave fluxes for climate monitoring and climate model validation. To achieve this goal, CERES relies on TOA broadband fluxes derived from geostationary satellite (GEO) imagery to account for the diurnal flux variations between the CERES observation intervals. Consistent global flux derivation depends on accurate and consistent cloud retrievals. Scene-dependent spectral measurement inconsistency of the instruments that make up the contiguous ring of GEO observations (GEO-Ring), as well as limb darkening effects, can cause discontinuities in derived cloud properties and radiative fluxes at the boundaries of adjacent imager domains. Although the algorithms utilize radiative transfer models to account for instrument-band-dependent atmospheric correction and viewing zenith angle (VZA) dependency, small discontinuities may persist due to uncertainties inherent to the multiple imager-specific algorithms. Furthermore, while hyperspectral-instrument-based spectral band adjustment factors may effectively account for spectrally induced bias, they are less effective at reducing variance owed to the specific composition of the viewed scene, which is challenging to robustly characterize. As such, this article highlights the use of a deep neural network (DNN) to resolve spectral-and VZA-induced biases between GEO-Ring imagers. The DNN uses available infrared (IR) channels from the GEO instruments, along with viewing and solar illumination geometry, to estimate homogenized, VIIRS-like IR radiances for use in the GEO cloud algorithm. This approach is effective at mitigating scene-dependent spectral variance and VZA dependency, resulting in consistent radiance measurements across the GEO-Ring, thereby leading toward a more seamless global cloud assessment.

deep learning↗

DOE OSTI2020

Achieving balanced execution through runtime detection of performance variation

Systems, apparatuses, and methods for achieving balanced execution in a multi-node cluster through runtime detection of performance variation are described. During a training phase, performance counters and an amount of time spent waiting for synchronization is monitored for a plurality of tasks for each node of the multi-node cluster. These values are utilized to generate a model which correlates the values of the performance counters to the amount of time spent waiting for synchronization. Once the model is built, the values of the performance counters are monitored for a period of time at the start of each task, and these values are input into the model. The model generates a prediction of whether a given node is on the critical path. If the given node is predicted to be on the critical path, the power allocation of the given node is increased.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Battery designs with high capacity anode materials to achieve desirable cycling properties

Improved high energy capacity designs for lithium ion batteries are described that take advantage of the properties of high specific capacity anode active compositions and high specific capacity cathode active compositions. In particular, specific electrode designs provide for achieving very high energy densities. Furthermore, the complex behavior of the active materials is used advantageously in a radical electrode balancing design that significantly reduced wasted electrode capacity in either electrode when cycling under realistic conditions of moderate to high discharge rates and/or over a reduced depth of discharge.

25 ENERGY STORAGE↗

DOE OSTI2021

Evaluation of Topology Optimization to Achieve Energy Savings at the Urban District Level: Preprint

Advanced district thermal energy systems have the potential to achieve significant energy savings and facilitate the integration of renewable thermal resources and waste heat, contributing to reductions in carbon emissions. Such systems, also known as fifth generation district heating and cooling (5GDHC) systems, circulate water at temperatures close to ambient, and leverage electrically-driven water-source heat pumps located at connected buildings to further temper the water. However, barriers exist to the adoption of 5GDHC systems, including the factorial growth in potential network configurations as a function of the number of considered buildings. Topology optimization, which seeks to answer the questions, “Which is the best subset of buildings, if any, to connect to a district thermal energy system, and by what network should they be connected, to minimize life cycle cost?” can accelerate the adoption of 5GDHC systems. This study is part of an effort to develop a topology optimization framework for district thermal energy systems. In this study, a heuristic for one aspect of the topology optimization problem---the use of the minimal spanning tree network to connect a given set of buildings at the least life cycle cost---is validated.

28 EE - Advanced Manufacturing Office (EE-5A)↗

DOE OSTI2021

State Insights On The Water-Energy Nexus And Policy Ideas To Achieve Greater Savings

Governors, state policymakers, utilities and other stakeholders across the country are increasingly aware of the connection between energy and water production and use, and the need to conserve both resources to meet economic and environmental goals. It requires substantial amounts of water to produce energy and considerable amounts of energy to treat and deliver water. The critical interdependence between energy and water was clearly illustrated during the recent winter storm in Texas and other parts of the South in February 2021. Initial power outages contributed to a longer-term water crisis. Power outages led to water pump failures while water demand increased from frozen water pipes that burst. This caused low water pressure that can lead to harmful bacteria growth in the water. The power outages also prevented water treatment plants from properly treating the water for several days, thereby leaving many residents without clean drinking water and worsening the storm’s impacts. The National Governors Association has been working with states on this connection between water and energy and strategies for conserving those resources for several years. NGA held a Water-Energy Nexus Learning Lab in September 2020. This event invited two leading states in the water-energy nexus space, Arizona and Wisconsin, to showcase some of their model policies and programs to other states, Maryland, Nevada, North Carolina, North Dakota, and Washington, looking for greater savings opportunities. This paper provides an overview of challenges that states are facing in developing integrated water and energy conservation policies; provides background on Arizona and Wisconsin’s innovative water-energy policies and programs; and summarizes action items the participating state teams identified for their respective states. The main categories of policy solutions identified by states at NGA’s Water-Energy Nexus Learning Lab were: Funding & Financing – providing financial incentives for water efficiency modeled after established energy efficiency programs, and an emphasis on financial support for small water and energy utilities. Education & Technical Assistance – providing more education and training opportunities about ways to achieve cost-effective energy and water savings, and the needs of resource-constrained small and medium utilities for training and other assistance. Structural Changes to Encourage Conservation – developing ways to incentivize agricultural conservation such as through water allocation strategies; adopting water reuse or water loss standards; and requiring electric utilities to consider water impacts as part of their integrated resource planning process. Communications & Data – conducting energy audits, reviewing water data provided to state agencies, and developing data benchmarking tools to measure and better manage energy and water use. Climate Strategy – establishing a multi-agency working group or other collaborative approach to determine ways to integrate energy and water savings in state policies and help meet the state climate objectives.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Getting to Zero—and Beyond: California’s aspiration to become the first carbon-negative state appears to be achievable and affordable.

As a response to mounting concerns about the consequences of unabated climate change, California established in 2018 an aspirational goal of achieving a completely carbon-neutral economy by 2045, and becoming carbon negative after that. The state has long championed climate-friendly policies such as using energy more efficiently, generating power from renewable sources, and putting cleaner cars on the road, among other emissions-reduction strategies. Unfortunately, California’s own evaluations indicate that even when these are successful—after intensive electrification of the economy and a drastic shift away from fossil fuels—there will remain substantial greenhouse gas emissions. The residuals come from widespread small sources that are hard to control, and from larger sources that cannot be controlled in time.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

A New Gold Mine? Achieving HVAC Energy Efficiency Through a System Metric

Washington State's Commercial Energy Code adopted a new energy metric called HVAC Total System Performance Ratio (TSPR) in 2019, a first in the codes world to regulate HVAC system efficiency. TSPR is a ratio of annual heating and cooling loads to the annual carbon emissions associated with the energy consumed by the HVAC system. TSPR provides a performance-based solution to evaluate and improve the overall HVAC design. The TSPR metric and its companion calculation tool were developed by Pacific Northwest National Laboratory (PNNL) with support from U.S. Department of Energy (DOE), Northwest Energy Efficiency Alliance (NEEA) and the City of Seattle. The new metric represents a significant shift in how HVAC design will meet code requirements. Utility programs can also leverage TSPR as a measure to determine energy savings and incentive amounts for HVAC retrofits. This paper describes the efforts by NEEA and its collaborators to prepare the market for TSPR adoption in code. This paper provides the pilot projects led by University of Washington Integrated Design Lab (IDL) to understand potential issues that could be faced by early adopters. This paper also covers how training and outreach provide engagement opportunities that can streamline code compliance, help address issues faced by early adopters and promote participation in utility programs. As Washington State works on the goals of 70% energy reduction and zero fossil-fuel greenhouse gas emission homes and buildings by the year 2031 , system level performance metrics will likely become increasingly more necessary and prevalent. This paper concludes that the HVAC TSPR requirement helps familiarize the HVAC industry with this approach and helps Washington achieve its long-term goals.

Liu, Bing↗

DOE OSTI2022

Achieving American Leadership in the Electric Grid Supply Chain Factsheet

The U.S. electric grid consists of more than 22,000 generators; 55,000 substations; 642,000 miles of high-voltage lines; and 6.3 million miles of distribution lines that serve 153 million customers. To date, much of the smart grid transformation has focused on applying advanced digital information and communication technologies to the power grid to improve the system’s efficiency, flexibility, and security. To achieve the full value of grid modernization, we also need advances in grid hardware. Many critical components supporting the power grid have limited to no domestic manufacturing capacity and face complex challenges in supporting a rapid expansion of the grid to meet multiple objectives, including decarbonization goals.

Source record↗

DOE OSTI2022

Achieving American Leadership in the Hydropower Supply Chain

In 2020, hydropower accounted for 36.7% of U.S. renewable electricity generation and 7.3% of total electricity generation. While the existing U.S. supply chain effectively supports the nation’s hydropower fleet—the fourth-largest in the world, alongside the third-largest pumped storage hydropower (PSH) fleet—refurbishments, upgrades, and new development are required to modernize and expand the fleet and facilitate a clean, emissions-free U.S. electricity grid by 2035. To achieve these goals, researchers compiled a report examining the U.S. hydropower energy supply chain, including raw materials, processed materials, components, subcomponents, and recycling.

Source record↗

DOE OSTI2022

Achieving American Leadership in the Wind Supply Chain Factsheet

Land-based and offshore wind are expected to be a cornerstone for achieving U.S. clean electricity generation objectives, including 100% clean electricity by 2035 and an 30 gigawatts (GW) of offshore wind by 2030. Meeting these goals will require significant expansion of domestic supply chains and installation of unprecedented amounts of wind capacity.

Source record↗