Search NASA⌕ Search

SEARCH · Search NASA

Results for “Analysi”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

ESnet Requirements Review Program Through the IRI Lens: A Meta-Analysis of Workflow Patterns Across DOE Office of Science Programs (Final Report)

The Department of Energy (DOE) ensures America’s security and prosperity by addressing its energy, environmental, and nuclear challenges through transformative science and technology solutions. The DOE’s Office of Science (SC) delivers groundbreaking scientific discoveries and major scientific tools that transform our understanding of nature and advance the energy, economic, and national security of the United States. The SC’s programs advance DOE mission science across a wide range of disciplines and have developed the research infrastructure needed to remain at the forefront of scientific discovery. The DOE SC’s world-class research infrastructure — exemplified by the 28 SC scientific user facilities — provides the research community with premier observational, experimental, computational, and network capabilities. Each user facility is designed to provide unique capabilities to advance core DOE mission science for its sponsor SC program and to stimulate a rich discovery and innovation ecosystem. Research communities gather and flourish around each user facility, bringing together diverse perspectives. A hallmark of many facilities is the large population of students, postdoctoral researchers, and early-career scientists who contribute as full-fledged users. These facility staff and users collaborate over years to devise new approaches to utilizing the user facility’s core capabilities. The history of the SC user facilities has many examples of wildly inventive researchers challenging operational orthodoxy to pioneer new vistas of discovery; for example, the use of the synchrotron X-ray light sources for study of proteins and other large biological molecules. This continual reinvention of the practice of science — as users and staff forge novel approaches expressed in research workflows — unlocks new discoveries and propels scientific progress. Within this research ecosystem, the high-performance computing (HPC) and networking user facilities stewarded by SC’s Advanced Scientific Computing Research (ASCR) program play a dynamic cross-cutting role, enabling complex workflows demanding high performance data, networking, and computing solutions. The DOE SC’s three HPC user facilities and the Energy Sciences Network (ESnet) high-performance research network serve all of the SC’s programs as well as the global research community. Argonne Leadership Computing Facility (ALCF), the National Energy Research Scientific Computing Center (NERSC), and Oak Ridge Leadership Computing Facility (OLCF) conceive, build, and provide access to a range of supercomputing, advanced computing, and large-scale data-infrastructure platforms, while ESnet interconnects DOE SC research infrastructure and enables seamless exchange of scientific data. All four facilities operate testbeds to expand the frontiers of computing and networking research. Together, the ASCR facilities enterprise seeks to understand and meet the needs and requirements across SC and DOE domain science programs and priority efforts, highlighted by the formal requirements reviews (RRs) methodology. In recent years, the research communities around the SC user facilities have begun experimenting with and demanding solutions integrated with HPC and data infrastructure. This rise of integrated-science approaches is documented in many community and high-level government reports. At the dawn of the era of exascale science and the acceleration of artificial intelligence (AI) innovation, there is a broad need for integrated computational, data, and networking solutions. In response to these drivers, DOE has developed a vision for an Integrated Research Infrastructure (IRI): To empower researchers to meld DOE’s world-class research tools, infrastructure, and user facilities seamlessly and securely in novel ways to radically accelerate discovery and innovation.

42 ENGINEERING↗
DOE OSTI2023

Editorial: Harmonizing life cycle analysis (LCA) and techno-economic analysis (TEA) guidelines: a common framework for consistent conduct and transparent reporting of carbon dioxide removal and CCU technology appraisal

Stabilizing the climate will require significant efforts to curb greenhouse gas emissions, manage emissions that cannot be avoided, and remove as many legacy emissions as possible [i.e., carbon dioxide (International Energy Agency, 2020; Author Collective, 2022)]. In that context, negative emissions technologies will take CO 2 from the air (Direct Air Capture) or the water (Direct Ocean Capture) and permanently remove it (Roger et al., 2021) either by sequestering the CO 2 underground or converting it to so-called Track 1 materials (Sick et al., 2021) that have lifetimes of >100 years. Shorter-lived products that decompose back into CO 2 in <100 years are categorized as Track 2 materials and will at best be carbon neutral. A carbon neutral status can also be achieved if captured CO 2 from fossil-based point sources is sequestered or used to create Track 1 materials. Conversion of CO 2 from fossil-based sources to any Track 2 material and subsequent decomposition would add new fossil-based carbon to the atmosphere, constituting an ultimately undesirable process. The overall carbon footprint of a process or product will depend on many factors associated with the carbon production, use, and disposal phases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Fast Quasi-Static Time-Series Simulation for Accurate PV Inverter Semiconductor Fatigue Analysis with a Long-Term Solar Profile

Power system simulations with long-term data typically have large time steps varying from one second to a few minutes. However, for PV inverter semiconductors, the minimum thermal stress cycle occurs over the fundamental grid frequency (50 or 60 Hz). This requires the time step of the fatigue simulation to be around 100 µs. This small time step requires long computation times to process yearly power production profiles. This paper proposes a fast fatigue simulation for inverter semiconductors using the quasi-static time series (QSTS) simulation concept. The proposed simulation calculates the steady state of the semiconductor junction temperature by using a Fast Fourier Transform (FFT). The small thermal cycling during a switching period and even over the fundamental waveform is disregarded to further accelerate the simulation speed. The resulting time step of the fatigue simulation is 15 minutes, which is consistent with the solar dataset. The error of the proposed simulation is 0.16% compared to the fatigue simulation results using the complete thermal stress profile. A PV inverter that responds to a Transactive Energy System (TES) is simulated to demonstrate the use of the proposed fatigue simulation. The proposed simulation has the potential to co-simulate with system level simulation tools that also adopt the QSTS concept.

Liu, Yunting↗
DOE OSTI2021

Diffraction Methods for Qualitative and Quantitative Texture Analysis of Ferroelectric Ceramics

Crystallographic textures are pervasive in ferroelectrics and underpin the functional properties of devices utilizing these materials because many macroscopic properties (e.g., piezoelectricity) require a non-random distribution of dipoles. Inducing a preferred grain texture has become a viable route to improve these functional properties. X-ray and neutron diffraction have become valuable tools to probe crystallographic textures. This paper presents an overview of qualitative and quantitative methods for assessing crystallographic textures in electroceramics (domain and grain textures) and discusses their strengths and weaknesses.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Optical analysis of III-nitride micro-light-emitting diodes with different sidewall treatments at low current density operation

Here, in this work, the optical efficiency of III-nitride blue micro-LEDs (μLEDs) ranged from 5 × 5 to 60 × 60 μm 2 with different sidewall treatments at low current density range was investigated. The results showed dielectric sidewall passivation using atomic layer deposition (ALD) has superior optical enhancement compared to conventional RF sputtering, where most of the enhancement occurred at low current density range. Additionally, the use of ALD sidewall passivation and chemical treatment offered significant efficiency improvement for different sizes of μLEDs at operating less than 1 A cm −2 and the devices without sidewall treatments did not emit light. The effect of sidewall treatments to the effective Shockley–Read–Hall (SRH) nonradiative recombination coefficient, or the effective A coefficient from the ABC model, was estimated. The effective SRH nonradiative recombination coefficient was suppressed by two orders of magnitude for devices with sidewall treatments compared to devices without sidewall passivation.

Wong, Matthew S.↗
DOE OSTI2020

DER Planning with Resilience Analysis Using REopt Lite: A Behind-the-Meter Techno-Economic Analysis Tool

REopt Lite is a techno-economic decision support model for behind-the-meter energy systems design and dispatch modeling. REopt Lite is used to optimize energy systems for buildings, campuses, communities, and microgrids. It is based on a Mixed Integer Linear Programming (MILP) optimization model. It is a fully automated and streamlined energy modeling tool that can be used off-the-shelf for a wide variety of distributed generation integration analyses and at the same time is architected to be extensible for user-specific customizations for advanced users and subject matter experts. It is publicly available as a webtool as well as has an Application Programming Interface (API). The API functionality enables programmatic access to the model facilitating smooth integration with other distribution systems modeling tools, and automated multiple scenarios/sensitivity studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗