Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “decadal prediction”

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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The age and potential causes of the giant Green Lake Landslide, Fiordland, New Zealand

Abstract Landslide deposits preserved in the geological record afford opportunities to better inform hillslope and seismic hazard and risk models, particularly in regions where observational records are short. In the Southern Alps of New Zealand, small coseismic landslides are frequent, but the geological record preserves several instances of more substantial (> 1 km 3 ) but infrequent mass failures. With an estimated volume of 27 km 3 , the giant Green Lake Landslide represents one of the largest subaerial landslides on Earth. Previous work has suggested this deep-seated mass movement was most likely triggered by high-intensity seismic shaking, but that local structural weakness and/or glacial debuttressing may help to explain the anomalously large failure volume. Resolving the potential contribution of the latter is important given predictions concerning alpine deglaciation in the coming decades to centuries. Key to resolution are secure chronologies of landslide emplacement and past glacier change. Here we present in situ cosmogenic 10 Be exposure ages from the Green Lake Landslide that suggest an emplacement age of 15.5 ± 0.7 ka. Recent work shows that glacial retreat in the region was underway by 19 ka, indicating that the Green Lake Landslide was emplaced 3–4 kyr after the onset of glacier retreat. Given the geometry of the former confining valley glacier, we expect that the deglaciation-landslide age gap is closer to the upper end of this estimate. If correct, this conclusion places greater weight on the roles of local geological structure and/or a great earthquake as factors contributing to the exceptionally large volume of this event.

58 GEOSCIENCES↗
DOE OSTI2026

Good practices for documenting AI-based studies on energy and buildings

Artificial intelligence has transformed building science research over the past decade, with applications spanning energy modeling, energy prediction, HVAC optimization and controls, fault detection, and occupancy modeling. However, many studies lack adequate documentation of datasets, algorithms, training procedures, and validation methods. Building science research faces additional challenges including inconsistent evaluation metrics, limited generalizability across building types, climates, and significant gaps between experimental studies and deployed systems. This communication provides practical guidance for good practices in documenting and publishing AI-based research following established standards from the computer science and machine learning communities. By adopting frameworks such as Datasheets for Datasets, Model Cards, and standardized reproducibility checklists, researchers can ensure their work meets the rigorous documentation standards necessary for reproducible, comparable, and impactful building science research.

Hong, Tianzhen [Lawrence Berkeley National Laborat↗
DOE OSTI2023

Shortwave absorption by wildfire smoke dominated by dark brown carbon

Abstract Wildfires emit large amounts of black carbon and light-absorbing organic carbon, known as brown carbon, into the atmosphere. These particles perturb Earth’s radiation budget through absorption of incoming shortwave radiation. It is generally thought that brown carbon loses its absorptivity after emission in the atmosphere due to sunlight-driven photochemical bleaching. Consequently, the atmospheric warming effect exerted by brown carbon remains highly variable and poorly represented in climate models compared with that of the relatively nonreactive black carbon. Given that wildfires are predicted to increase globally in the coming decades, it is increasingly important to quantify these radiative impacts. Here we present measurements of ensemble-scale and particle-scale shortwave absorption in smoke plumes from wildfires in the western United States. We find that a type of dark brown carbon contributes three-quarters of the short visible light absorption and half of the long visible light absorption. This strongly absorbing organic aerosol species is water insoluble, resists daytime photobleaching and increases in absorptivity with night-time atmospheric processing. Our findings suggest that parameterizations of brown carbon in climate models need to be revised to improve the estimation of smoke aerosol radiative forcing and associated warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Prediction of unconventional magnetism in doped FeSb 2

Significance For many decades, it has been commonly believed that all electronic states of a collinear antiferromagnet (AF) are spin-degenerate, unless the underlying crystal structure lacks centrosymmetry and has spin–orbit coupling. This has been essentially definitional for antiferromagnetism and is widely used experimentally to distinguish ferromagnets from AFs. Recently, it was demonstrated that a new class of magnets, possessing antiferromagnetic order and without net magnetization but showing a typical ferromagnetic response in many aspects, is possible. We predict that F e S b 2 , which is well known but poorly understood magnetically, is an incipient unconventional magnet of this type and can be pushed to become one by Co or Cr doping. Moreover, the calculated magnetic anisotropy is favorable for exhibiting various anomalous properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Time-dependent density-functional-theory calculations of the nonlocal electron stopping range for inertial confinement fusion applications

Nonlocal electron transport is important for understanding laser-target coupling for laser-direct-drive (LDD) inertial confinement fusion (ICF) simulations. Current models for the nonlocal electron mean free path in radiation-hydrodynamic codes are based on plasma-physics models developed decades ago; improvements are needed to accurately predict the electron conduction in LDD simulations of ICF target implosions. Here we utilized time-dependent density functional theory (TD-DFT) to calculate the electron stopping power (SP) in the so-called conduction-zone plasmas of polystyrene in a wide range of densities and temperatures relevant to LDD. Compared with the modified Lee-More model, the TD-DFT calculations indicated a lower SP and a higher stopping range for nonlocal electrons. We fit these electron SP calculations to obtain a global analytical model for the electron stopping range as a function of plasma conditions and the nonlocal electron kinetic energy. This model was implemented in the one-dimensional radiation-hydrodynamic code LILAC to perform simulations of LDD ICF implosions, which are further compared with simulations by the standard modified Lee-More model. In conclusion, results from these integrated simulations are discussed in terms of the implications of this TD-DFT-based mean-free-path model to ICF simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Accelerated Creep Testing of Inconel 718 Using the Stepped Isostress Method (SSM)

This paper demonstrates the stepped isostress method (SSM); an accelerated creep test (ACT) for the rapid assessment of metallic materials. The SSM test is based on the time-temperature-stress superposition principle (TTSSP) where temperature and/or stress are step increased to accelerate the time-to-rupture. The SSM test has proven successful for the ACT of polymers and polymeric composites but has yet to be proven for metallic materials. In this study, new test matrix design rules for the SSM of metals are established based on deformation mechanism, time-temperature transformation, and time-temperature precipitation maps. A test matrix of SSM and conventional creep tests (CCTs) are executed for alloy Inconel 718 at 750°C (1382°F) with stress levels ranging from 100 to 350 MPa. Validation CCT data is gathered from the Japan National Institute of Material Science (NIMS). Material constants for the Sine-hyperbolic (Sinh) constitutive model are calibrated using the SSM data and employed to predict the conventional creep response. Here, when blindly compared to the CCT data, the SSM calibrated Sinh model can accurately predict the conventional creep response across logarithmic decades and thus accelerate the capture of conventional creep data. Fractography indicates ductile fracture by transgranular microvoid coalescence (TMVC) with the same fracture mode observed in both SSM and CCT specimens. Creep cavitation is indicated by the population, smoothness, and size of microvoids.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Feedback, physics, and forecasts: The emerging paradigm of machine learning-driven battery research

Machine learning (ML) is reshaping how we understand, predict, and optimize electrochemical systems. In batteries, ML accelerates discovery across chemistry, design, and operation by transforming massive experimental and simulated datasets into predictive, interpretable models. This review consolidates a decade of progress in ML-driven battery innovation, from early-cycle feature extraction to operando image analysis and physics-informed modeling. We categorize approaches by data domain and physical fidelity, emphasizing interpretable ML for diagnostics, reinforcement learning for control, and multi-objective optimization for lifetime extension strategies. Additionally, we demonstrate how integrated models accelerate discovery, reduce testing time, and guide sustainable design. Economic analyses furthermore illustrate how these advances can lower cost per cycle and improve circularity. Together, these developments chart a path toward self-optimizing, sustainable battery technologies.

artificial intelligence↗
DOE OSTI2020

Spectroscopic Studies of 30 Short-period Cataclysmic Variable Stars and Remarks on the Evolution and Population of Similar Objects

We present spectroscopy and orbital periods P {sub orb} for 30 apparently nonmagnetic cataclysmic binaries with periods below ∼3 hr, nearly all of which are dwarf novae, mostly of the SU Ursae Majoris subclass. We then turn to the evidence supporting the prediction that short-period dwarf novae evolve toward longer periods after passing through a minimum period—the “period bounce” phenomenon. Plotting data from the literature reveals that for superhump period excess ϵ = (P {sub sh} − P {sub orb})/P {sub orb} below ∼0.015, the period appears to increase with decreasing ϵ, agreeing at least qualitatively with the predicted behavior. Next, motivated by the long (decadal) outburst intervals of the WZ Sagittae subclass of short-period dwarf novae, we ask whether there could be a sizable population of “lurkers”—systems that resemble dwarf novae at minimum light, but which do not outburst over accessible timescales (or at all) and therefore do not draw attention to themselves. By examining the outburst history of the Sloan Digital Sky Survey sample of CVs, which were selected by color and not by outburst, we find that a large majority of the color-selected dwarf-nova-like objects have been observed to outburst, and we conclude that “lurkers,” if they exist, are a relatively minor part of the CV population.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2006

The Impact of Microphysics on Intensity and Structure of Hurricanes

During the past decade, both research and operational numerical weather prediction models, e.g. Weather Research and Forecast (WRF) model, have started using more complex microphysical schemes originally developed for high-resolution cloud resolving models (CRMs) with a 1-2 km or less horizontal resolutions. WFW is a next-generation mesoscale forecast model and assimilation system that has incorporated modern software framework, advanced dynamics, numeric and data assimilation techniques, a multiple moveable nesting capability, and improved physical packages. WFW model can be used for a wide range of applications, from idealized research to operational forecasting, with an emphasis on horizontal grid sizes in the range of 1-10 km. The current WRF includes several different microphysics options such as Lin et al. (1983), WSM 6-class and Thompson microphysics schemes. We have recently implemented three sophisticated cloud microphysics schemes into WRF. The cloud microphysics schemes have been extensively tested and applied for different mesoscale systems in different geographical locations. The performances of these schemes have been compared to those from other WRF microphysics options. We are performing sensitivity tests in using WW to examine the impact of six different cloud microphysical schemes on hurricane track, intensity and rainfall forecast. We are also performing the inline tracer calculation to comprehend the physical processes @e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes.

Tao, Wei-Kuo↗
NASA NTRS2007

The Impact of Microphysics on Intensity and Structure of Hurricanes and Mesoscale Convective Systems

During the past decade, both research and operational numerical weather prediction models, e.g. Weather Research and Forecast (WRF) model, have started using more complex microphysical schemes originally developed for high-resolution cloud resolving models (CRMs) with a 1-2 km or less horizontal resolutions. WRF is a next-generation mesoscale forecast model and assimilation system that has incorporated modern software framework, advanced dynamics, numeric and data assimilation techniques, a multiple moveable nesting capability, and improved physical packages. WRF model can be used for a wide range of applications, from idealized research to operational forecasting, with an emphasis on horizontal grid sizes in the range of 1-10 km. The current WRF includes several different microphysics options such as Purdue Lin et al. (1983), WSM 6-class and Thompson microphysics schemes. We have recently implemented three sophisticated cloud microphysics schemes into WRF. The cloud microphysics schemes have been extensively tested and applied for different mesoscale systems in different geographical locations. The performances of these schemes have been compared to those from other WRF microphysics options. We are performing sensitivity tests in using WRF to examine the impact of six different cloud microphysical schemes on precipitation processes associated hurricanes and mesoscale convective systems developed at different geographic locations [Oklahoma (IHOP), Louisiana (Hurricane Katrina), Canada (C3VP - snow events), Washington (fire storm), India (Monsoon), Taiwan (TiMREX - terrain)]. We will determine the microphysical schemes for good simulated convective systems in these geographic locations. We are also performing the inline tracer calculation to comprehend the physical processes (i.e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes and mesoscale convective systems.

Tao, Wei-Kuo↗
NASA NTRS2007

An Improved Bulk Microphysical Scheme for Studying Precipitation Processes: Comparisons with Other Schemes

Cloud microphysical processes play an important role in non-hydrostatic high-resolution simulations. Over the past decade both research and operational numerical weather prediction models have started using more complex cloud microphysical schemes that were originally developed for high-resolution cloud-resolving models. An improved bulk microphysical parameterization (adopted from the Goddard microphysics schemes) has recently implemented into the Weather Research and Forecasting (WRF) model. This bulk microphysical scheme has three different options --- 2ICE (cloud ice & snow), 3ICE-graupel (cloud ice, snow & graupel) and 3ICE-hail (cloud ice, snow & hail). High-resolution model simulations are conducted to examine the impact of microphysical schemes on two different weather events (a midlatitude linear convective system and an Atlantic hurricane). In addition, this bulk microphysical parameterization is compared with WIRF's three other bulk microphysical schemes.

Tao, W. K.↗
NASA NTRS2011

The Impact of Microphysical Schemes on Hurricane Intensity and Track

During the past decade, both research and operational numerical weather prediction models [e.g. the Weather Research and Forecasting Model (WRF)] have started using more complex microphysical schemes originally developed for high-resolution cloud resolving models (CRMs) with 1-2 km or less horizontal resolutions. WRF is a next-generation meso-scale forecast model and assimilation system. It incorporates a modern software framework, advanced dynamics, numerics and data assimilation techniques, a multiple moveable nesting capability, and improved physical packages. WRF can be used for a wide range of applications, from idealized research to operational forecasting, with an emphasis on horizontal grid sizes in the range of 1-10 km. The current WRF includes several different microphysics options. At NASA Goddard, four different cloud microphysics options have been implemented into WRF. The performance of these schemes is compared to those of the other microphysics schemes available in WRF for an Atlantic hurricane case (Katrina). In addition, a brief review of previous modeling studies on the impact of microphysics schemes and processes on the intensity and track of hurricanes is presented and compared against the current Katrina study. In general, all of the studies show that microphysics schemes do not have a major impact on track forecasts but do have more of an effect on the simulated intensity. Also, nearly all of the previous studies found that simulated hurricanes had the strongest deepening or intensification when using only warm rain physics. This is because all of the simulated precipitating hydrometeors are large raindrops that quickly fall out near the eye-wall region, which would hydrostatically produce the lowest pressure. In addition, these studies suggested that intensities become unrealistically strong when evaporative cooling from cloud droplets and melting from ice particles are removed as this results in much weaker downdrafts in the simulated storms. However, there are many differences between the different modeling studies, which are identified and discussed.

Tao, Wei-Kuo↗
NASA NTRS2010

The Impact of Microphysical Schemes on Intensity and Track of Hurricane

During the past decade, both research and operational numerical weather prediction models [e.g. Weather Research and Forecasting Model (WRF)] have started using more complex microphysical schemes originally developed for high-resolution cloud resolving models (CRMs) with a 1-2 km or less horizontal resolutions. The WRF is a next-generation meso-scale forecast model and assimilation system that has incorporated a modern software framework, advanced dynamics, numeric and data assimilation techniques, a multiple moveable nesting capability, and improved physical packages. The WRF model can be used for a wide range of applications, from idealized research to operational forecasting, with an emphasis on horizontal grid sizes in the range of 1-10 km. The current WRF includes several different microphysics options. At Goddard, four different cloud microphysics schemes (warm rain only, two-class of ice, two three-class of ice with either graupel or hail) are implemented into the WRF. The performances of these schemes have been compared to those from other WRF microphysics scheme options for an Atlantic hurricane case. In addition, a brief review and comparison on the previous modeling studies on the impact of microphysics schemes and microphysical processes on intensity and track of hurricane will be presented. Generally, almost all modeling studies found that the microphysics schemes did not have major impacts on track forecast, but did have more effect on the intensity. All modeling studies found that the simulated hurricane has rapid deepening and/or intensification for the warm rain-only case. It is because all hydrometeors were very large raindrops, and they fell out quickly at and near the eye-wall region. This would hydrostatically produce the lowest pressure. In addition, these modeling studies suggested that the simulated hurricane becomes unrealistically strong by removing the evaporative cooling of cloud droplets and melting of ice particles. This is due to the much weaker downdraft simulated. However, there are many differences between different modeling studies and these differences were identified and discussed.

Tao, W. K.↗
NASA NTRS2017

Re-Tooling the Agency's Engineering Predictive Practices for Durability and Damage Tolerance

Over the past decade, the Agency has placed less emphasis on testing and has increasingly relied on computational methods to assess durability and damage tolerance (D&DT) behavior when evaluating design margins for fracture-critical components. With increased emphasis on computational D&DT methods as the standard practice, it is paramount that capabilities of these methods are understood, the methods are used within their technical limits, and validation by well-designed tests confirms understanding. The D&DT performance of a component is highly dependent on parameters in the neighborhood of the damage. This report discusses D&DT method vulnerabilities.

Piascik, Robert S.↗
DOE OSTI2025

A Roadmap for the Future of Systems Biology in Cancer Research

Cancer systems biology seeks to understand how cancer arises as a system of interconnected molecules, cells, and tissues, with the goal of understanding, predicting, and controlling the disease. In the last decade, the field has rapidly grown as advances in experimental, computational, and analytic technologies have improved our ability to capture and recapitulate the complexities of cancer at multiple scales. However, the field’s promise to understand how specific molecular changes give rise to altered cancer outcomes remains incompletely fulfilled. Fortunately, an opportunity exists to accelerate progress by better coordinating modeling and data-gathering efforts across the cancer systems biology community. This will create the foundation for building accurate, multiscale cancer models that can better predict and identify improved therapeutic interventions. Here, in this study, we outline some of the current challenges in cancer systems biology research, how they can be addressed, and actions that the community can take to accelerate progress in the field.

Modeling & Simulation↗
DOE OSTI2024

Meteorological characteristics of extreme ozone pollution events in China and their future predictions

Ozone (O 3 ) has become one of the most concerning air pollutants in China in recent decades. In this study, based on surface observations, reanalysis data, global atmospheric chemistry model simulations, and multi-model future predictions, meteorological characteristics conducive to extreme O 3 pollution in various regions of China are investigated, and their historical changes and future trends are analyzed. During the most severe O 3 polluted months, the chemical production of O 3 is enhanced under the hot and dry conditions over the North China Plain (NCP) in June 2018 and the Yangtze River Delta (YRD) in July 2017, while regional transport is the main reason for the severe O3 pollution over the Sichuan Basin (SCB) in July 2015 and the Pearl River Delta (PRD) in September 2019. Over the last 4 decades, the frequencies of high-temperature and low-relative-humidity conditions increased in 2000–2019 relative to 1980–1999, indicating that O 3 pollution in both the NCP and YRD has become more frequent under historical climate change. In the SCB and PRD, the occurrence of atmospheric circulation patterns similar to those during the most polluted months increased, together with the more frequent hot and dry conditions, contributing to the increases in severe O 3 pollution in the SCB and PRD during 1980–2019. In the future (by 2100), the frequencies of months with anomalous high temperature show stronger increasing trends in the high-forcing scenario (Shared Socioeconomic Pathway (SSP5-8.5)) compared to the sustainable scenario (SSP1-2.6) in China. It suggests that high anthropogenic forcing will not only lead to slow economic growth and climate warming but also likely result in environmental pollution issues.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

Ecological Forecasting in the Applied Sciences Program and Input to the Decadal Survey

Ecological forecasting uses knowledge of physics, ecology and physiology to predict how ecosystems will change in the future in response to environmental factors. Further, Ecological Forecasting employs observations and models to predict the effects of environmental change on ecosystems. In doing so, it applies information from the physical, biological, and social sciences and promotes a scientific synthesis across the domains of physics, geology, chemistry, biology, and psychology. The goal is reliable forecasts that allow decision makers access to science-based tools in order to project changes in living systems. The next decadal survey will direct the development Earth Observation sensors and satellites for the next ten years. It is important that these new sensors and satellites address the requirements for ecosystem models, imagery, and other data for resource management. This presentation will give examples of these model inputs and some resources needed for NASA to continue effective Ecological Forecasting.

Ecology↗