Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “temperature extremes”

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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Advanced Manufacturing Techniques and Compositions of High Entropy Alloys for Nuclear Applications

In line with the objectives of the Department of Energy, Office of Nuclear Energy, Advanced Materials and Manufacturing Technologies (AMMT) program, this work focuses on new materials development and qualification research and development for next-generation, high-temperature nuclear reactors. High entropy alloys (HEAs) have the potential to serve in these extreme environments of next-generation nuclear reactors because of their unique phase transformation pathways and nanoscale and mesoscale microstructures. The current work focuses on understanding such nuclear-energy-relevant HEAs through a detailed literature survey, selected experimental work, and developing a decision matrix with criteria for the identification of HEAs that may have the most impact and value for further examination.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Comparison of Ion and Neutron Irradiations to 3 dpa at 500C in Ferritic-Martensitic Alloys

The growing global demand for energy will increasingly call upon advanced nuclear fission reactors to supply safe and reliable electricity. The structural and fuel cladding components of these reactors will be subject to extreme conditions of irradiation damage up to several hundred displacements per atom (dpa) at temperatures as high as 700°C. Ferritic-martensitic (F-M) steels are leading candidates for these challenging conditions due to their strength and dimensional stability under irradiation. In order to accelerate the process for evaluating F-M alloys, charged particles are increasingly being used to emulate neutron irradiations. Charged particle irradiations allow the possibility of conducting irradiation experiments within a shorter time period (i.e. at a rate up to 4 orders of magnitude faster) and with minimal radioactivation of the material, enabling lower cost and faster turnaround of post irradiation examination and analysis. However, the irradiation dose rate, damage cascade morphologies, and irradiation damage depth profiles all differ widely between protons, heavier ions, and neutrons. Currently, there is limited understanding of the significance of these physical differences and how they manifest in the irradiated microstructure and mechanical properties of F-M steels. The objective of this study is to evaluate charged particles as a surrogate for neutron irradiations in F-M alloys by assessing common irradiation conditions using Fe++ ions, protons, and neutrons. Keeping the temperature and dose consistent enables isolation of the effects of each irradiating particle and their respective dose rates and cascade morphologies.

Swenson, M.J.↗
DOE OSTI2025

Rapid Oxidation of Uranium Steel Alloys: Combustion Synthesis

This project explored the use of combustion synthesis as a rapid, high-temperature method for oxidizing uranium-bearing steel alloys. Traditional laboratory-scale synthesis methods often fail to replicate the thermal and kinetic conditions experienced by real-world particulates, particularly those formed under rapid quenching or high-temperature scenarios. Combustion synthesis offers a promising alternative by enabling fast, localized heating and flexible precursor selection. A series of targeted experiments were conducted using a U 2 NiCrFe 4 alloy as the precursor. The alloy was oxidized using combustion synthesis reactions fueled by uranyl nitrate and glycine, achieving peak temperatures exceeding 1,200 °C. Postreaction analysis using scanning electron microscopy (SEM), elemental mapping, and Raman spectroscopy revealed the formation of iron-based oxides, with limited but detectable evidence of uranium oxide phases such as UO 2 . The results indicate that under the rapid reaction and cooling conditions of combustion synthesis, iron oxides form preferentially, but uranium oxide formation is kinetically limited. These findings validate combustion synthesis as a viable method for simulating the oxidation behavior of uranium steels in extreme environments and lay the groundwork for future studies aimed at enhancing uranium oxide formation through higher temperatures or modified precursor compositions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Generalizability of heat-related health risk associations observed in a large healthcare claims database of patients with commercial health insurance

Extreme ambient heat is unambiguously associated with higher risk of illness and death. The Optum Labs Data Warehouse (OLDW), a database of medical claims from US-based patients with commercial or Medicare Advantage health insurance, has been used to quantify heat-related health impacts. Whether results for the insured sub-population are generalizable to the broader population has to our knowledge not been documented. We sought to address this question, for the US population in California from 2012 to 2019. We examined changes in daily rates of emergency department (ED) encounters and in-patient hospitalization encounters for all-causes, heat-related outcomes, renal disease, mental/behavioral disorders, cardiovascular disease, and respiratory disease. OLDW was the source for health data for insured individuals in California, and health data for the broader population were gathered from the California Department of Health Care Access and Information (HCAI). We defined extreme heat exposure as any day in a group of 2 or more days with maximum temperatures exceeding the county-specific 97.5 th percentile and used a space-time-stratified case–crossover design to assess and compare the impacts of heat on health. Average incidence rates of medical encounters differed by dataset. However, rate ratios for ED encounters were similar across datasets for all causes (ratio of incidence rate ratios (rIRR) = 0.989; 95% confidence interval (CI) = 0.973, 1.011), heat-related causes (rIRR = 1.080; 95% CI = 0.999, 1.168), renal disease (rIRR = 0.963; 95% CI = 0.718, 1.292), and mental health disorders (rIRR = 1.098; 95% CI = 1.004, 1.201). Rate ratios for inpatient encounters were also similar. This work presents evidence that OLDW can continue to be a resource for estimating the health impacts of extreme heat.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Characterization of Long-term Service Coal Combustion Power Plant Extreme Environment Materials

The technical goal of this project is to develop a comprehensive database of mechanical properties, alloy microstructures, and to a lesser extent, the oxidation/corrosion behavior of coal-fired power plant components, such as boiler tubing, steam headers and steam piping, which have been in long-term service (at least 100,000 operating hours, and preferably more than 200,000 operating hours) under the operating conditions of high temperatures and high mechanical stresses where creep, fatigue, steam-side oxidation, and fireside corrosion are life-limiting factors. The components included in the database will include the following types of high temperature alloys: creep strength enhanced ferritic (CSEF) steels, 300-series H-grade stainless steels, and dissimilar metal welds (DMWs).

Characterization↗
DOE OSTI2026

Water Vapor Resistant SiC/SiC Composite for Hydrogen-Based Turbines (Final Scientific Technical Report)

New material innovations are needed for the extreme environments of next generation, hydrogen-fueled turbine engines. Ceramic matrix composites (CMCs) offer high-temperature capability but are susceptible to degradation in high-temperature water vapor. Pratt & Whitney’s (P&W) baseline silicon carbide (SiC)/SiC CMC was initially applied to design a component in a hydrogen-fueled engine, verifying the existence of a design space and extracting boundary conditions to inform testing parameters. Several material innovations, including two fibers, interface coatings (IFC), and self-healing matrices (SHM), were investigated to improve high-temperature performance in water vapor. A boron-doped pyrocarbon (B-PyC) IFC and a SHM matrix with layers of zirconium nitride (ZrN) or zirconium diboride (ZrB 2 ) were developed to fabricate minicomposites with either standard Hi-Nicalon™ Type S (HNS) fibers or new Tyranno® SA4 fibers (SA4). The B-PyC IFC is functional but lacks in providing improved durability. A matrix consisting of thick layers of SiC and thin layers of ZrB 2 shows promise as a SHM that can effectively seal matrix cracks in this extreme environment. Minicomposites with HNS fibers generally outperform those with SA4 fibers.

08 HYDROGEN↗
DOE OSTI2021

Hybridizing Machine Learning and Physically-based Earth System Models to Improve Prediction of Multivariate Extreme Events (AI Exploration of Wildland Fire Prediction)

Focal Areas: This project responds to two focal areas identified in the DOE Call for AI4ESP White Papers: 1) Predictive modeling through the use of artificial intelligence (AI) techniques, and 2) insights gleaned from complex data using explainable AI and big data analytics. Science Challenge: Large wildland fires (hereafter wildfires) appearing as high-impact compound climate extreme events are closely related to hydroclimate and water cycle extremes that modulate surface fuel supply and combustibility. These compound events have multivariate climatic features (e.g., temperature, precipitation, relative humidity, wind, lightning) and societal drivers (e.g., forest management, land use change, human caused ignitions). Meanwhile, they induce strong feedbacks to the coupled atmosphere, biosphere, and hydrosphere by perturbing regional and global radiation budget as well as ecological, biogeochemical, and water cycles across multiple spatiotemporal scales. The nonlinear interactions between these natural and anthropogenic components of the Earth system are too complex to be completely and adequately represented in today’s Earth system models (ESMs). The inherent stochastic nature of fire activity at all scales further increases the difficulty of its prediction using ESMs that are usually developed from deterministic equations and parameterizations. Besides, concurrence of long-term (decadal to interdecadal) global climate change and fire regime shifts overlapping with short-term (intraseasonal to interannual) variations of regional fire weather and burning activity confound predictability of these compound extreme events. We propose to address the above scientific challenges by using machine learning (ML)-based data-driven modeling techniques to integrate observations and physically-based ESMs’ simulations in a computationally efficient hybrid prediction system. This prediction system is supposed to characterize the wildfire’s sensitivity to climate and exogenous drivers at high resolution (~ 0.25°) on subseasonal to seasonal (S2S) timescales providing improved predictability and explainability. We will use the system to help identify: (1) What are the computational elements of a hybrid system needed to predict compound climate extreme events such as global wildfires? (2) What are the key drivers (either natural or anthropogenic) that modulate short-term variations of multivariate fire weather and burning activity over different regions? How can one take advantage of those driver-response relationships to improve the predictability of large wildfires on S2S time scales? (3) What are the underlying physical mechanisms and sources of improved predictability? Which ML techniques are optimal in revealing and adapting these mechanisms?

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Milestone Report: Effect of High Temperature CO 2 on Haynes 230 Alloy

The supercritical carbon dioxide (sCO 2 ) Brayton cycle is a promising candidate for future nuclear reactors due to its ability to improve power cycle energy conversion efficiency. The sCO 2 Brayton cycle can operate with an efficiency of 45-50% at operating temperatures of 550-700 C. One of the greatest hurdles currently faced by sCO 2 Brayton cycles is the extreme corrosivity of sCO 2 . This affects the longevity of the power cycle and thus the levelized cost of electricity. Past studies have shown that sCO 2 corrosion occurs through the formation of metal carbonates, oxide layers, and carburization, and alloys with Cr, Mo and Ni generally exhibit less corrosion. While stainless steels may offer sufficient corrosion resistance at the lower range of temperatures seen by the sCO 2 Brayton cycles, more expensive alloys such as Inconel and Haynes are typically needed for the higher temperature regions. This study investigates the effects of corrosion on the Haynes 230 alloy, focusing on changes in the mechanical properties.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Remarkable low-energy properties of the pseudogapped semimetal Be 5 Pt

We report measurements and calculations on the properties of the intermetallic compound Be 5 Pt. High-quality polycrystalline samples show a nearly constant temperature dependence of the electrical resistivity over a wide temperature range. On the other hand, relativistic electronic structure calculations indicate the existence of a narrow pseudogap in the density of states arising from accidental approximate Dirac cones extremely close to the Fermi level. A small true gap of order ~ 3 meV is present at the Fermi level, yet the measured resistivity is nearly constant from low to room temperature. We argue that this unexpected behavior can be understood by a cancellation of the energy dependence of density of states and relaxation time due to disorder, and discuss a model for electronic transport. With applied pressure, the resistivity becomes semiconducting, consistent with theoretical calculations that show that the band gap increases with applied pressure. We further discuss the role of Be inclusions in the samples.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Design of high-pressure iron Rayleigh–Taylor strength experiments for the National Ignition Facility

Iron is an important metal, scientifically and technologically. It is a common metal on Earth, forming the main constituent of the planet's inner core, where it is believed to be in solid state at high pressure and high temperature. It is also the main component of many important structural materials used in quasistatic and dynamic conditions. Laser-driven Rayleigh–Taylor instability provides a means of probing material strength at high pressure and high temperature. The unavoidable phase transition in iron at relatively low pressure induces microstructural changes that ultimately affect its strength in this extreme regime. This inevitable progression can make it difficult to design experiments and understand their results. Here, we address this challenge with the introduction of a new approach: a direct-drive design for Rayleigh–Taylor strength experiments capable of reaching up to 400 GPa over a broad range of temperatures. We use 1D and 2D hydrodynamic simulations to optimize target components and laser pulse shape to induce the phase transition and compress the iron to high pressure and high temperature. At the simulated pressure–temperature state of 350 GPa and 4000 K, we predict a ripple growth factor of 3–10 depending on the strength with minimal sensitivity to the equation of state model used. The growth factor is the primary observable, and the measured value will be compared to simulations to enable the extraction of the strength under these conditions. These experiments conducted at high-energy laser facilities will provide a unique way to study an important metal.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Newton trust-region methods with primary variable switching for simulating high temperature multiphase porous media flow

Coupling multiphase flow with energy transport due to high temperature heat sources introduces significant new challenges since boiling and condensation processes can lead to dry-out conditions with subsequent re-wetting. The transition between two-phase and single-phase behavior can require changes to the primary dependent variables adding discontinuities as well as extending constitutive nonlinear relations to extreme physical conditions. Practical simulations of large-scale engineered domains lead to Jacobian systems with a very large number of unknowns that must be solved efficiently using iterative methods in parallel on high-performance computers. Performance assessment of potential nuclear repositories, carbon sequestration sites and geothermal reservoirs can require numerous Monte-Carlo simulations to explore uncertainty in material properties, boundary conditions, and failure scenarios. Due to the numerical challenges, standard NR iteration may not converge over the range of required simulations and require more sophisticated optimization method like trust-region. In this study, we use the open-source simulator PFLOTRAN for the important practical problem of the safety assessment of future nuclear waste repositories in the U.S. DOE geologic disposal safety assessment Framework. The simulator applies the PETSc parallel framework and a backward Euler, finite volume discretization. We demonstrate failure of the conventional NR method and the success of trust-region modifications to Newton’s method for a series of test problems of increasing complexity. Trust-region methods essentially modify the Newton step size and direction under some circumstances where the standard NR iteration can cause the solution to diverge or oscillate. Furthermore, we show how the Newton Trust-Region method can be adapted for Primary Variable Switching (PVS) when the multiphase state changes due to boiling or condensation. The simulations with high-temperature heat sources which led to extreme nonlinear processes with many state changes in the domain did not converge with NR, but they do complete successfully with the trust-region methods modified for PVS. This implementation effectively decreased weeks of simulation time needing manual adjustments to complete a simulation down to a day. Finally, we show the strong scalability of the methods on a single node and multiple nodes in an HPC cluster.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Stretchable and Self‐Healable Semiconductive Composites Based on Hydrogen Bonding Cross‐linked Elastomeric Matrix

Abstract Semiconductors with both high stretchability and self‐healing capability are highly desirable for various wearable devices. Much progress has been achieved in designing highly stretchable semiconductive polymers or composites. The demonstration of self‐healable semiconductive composite is still rare. Here, an extremely soft, highly stretchable, and self‐healable hydrogen bonding cross‐linked elastomer, amide functionalized‐polyisobutylene (PIB‐amide) is developed, to enable a self‐healable semiconductive composite through compounding with a high‐performance conjugated diketopyrrolopyrrole (DPP‐T) polymer. The composite, consisting of 20% DPP‐T and 80% PIB‐amide, shows record high crack‐onset strain (COS ≈1500%), extremely low elastic modulus (E≈1.6 MPa), and unique ability to spontaneously self‐heal atroom temperature within 5 min. Unlike previous works, these unique composite materials also show strain‐independent charge mobility. An in‐depth morphological study based on multi‐model techniques indicate that all composites show blending ratio‐ and stretching‐independent fibril‐like aggregation due to the strong hydrogen bond in elastomer to enable the unique stable charge mobility. This study provides a new direction to develop highly healable and electronically stable semiconductive composite and will enable new applications of stretchable electronics.

Chemistry↗
DOE OSTI2024

Small Cells with Big Photosynthetic Productivities: Biotechnological Potential of the Picochlorum Genus

The Picochlorum genus is a distinctive eukaryotic green-algal clade that is the focus of several current biotechnological studies. It is capable of extremely rapid growth rates and has exceptional tolerances to high salinity, intense light, and elevated temperatures. Importantly, it has robust stability and high-biomass productivities in outdoor field trials in seawater. These features have propelled Picochlorum into the spotlight as a promising model for both fundamental and biotechnological research. Recently, several genetic tools, including genome editing, were developed for these algae, enabling insights into Picochlorum photophysiology and algal transformations for expanded capabilities. Here, we survey the Picochlorum genus, its genetic toolbox, recently characterized transformants, and discuss the commercial potential of Picochlorum as a salt-water photoautotrophic biocatalyst.

09 BIOMASS FUELS↗
DOE OSTI2023

Polynitrogen High Energy Density Materials Synthesized by Nonequilibrium Plasma

Metal pentazolate compounds that contain 5-nitrogen singly charged anion rings are an interesting class of materials from a thermodynamics perspective. These compounds are believed to be equilibrium phases only at extremely high pressures, and thus, they constitute exotic states of matter at ambient pressure and temperature. Moreover, the energy released by these pentazolate compounds upon relaxation to the equilibrium state at ambient conditions is in the range 1 to 10 MJ per kg, rivaling that of combustion reactions. The synthesis of pentazolates is not an easy task, and there are only two known methods, each of which has significant challenges. Here, the development of new scalable synthesis routes could enable the production of these exotic materials in sufficient quantity to explore their properties more widely beyond the context of explosives and propellants. In this Perspective, it is argued that nonequilibrium plasma is a promising reaction medium for the synthesis of metal pentazolate compounds, for example from the corresponding metal azide and N 2 gas activated by the discharge at low background temperature.

Chemical reactions↗
DOE OSTI2020

Distortions of the Rain Distribution With Warming, With and Without Self-Aggregation

We investigate how mesoscale circulations associated with convective aggregation can modulate the sensitivity of the hydrologic cycle to warming. We quantify changes in the full distribution of rain across radiative-convective equilibrium states in a cloud-resolving model. For a given Sea Surface Temperature (SST), the shift in mean rainfall between disorganized and organized states is associated with a shift in atmospheric radiative cooling, and is roughly analogous to the effect of a 4K SST increase. With rising temperatures, the increase in mean rain rate is insensitive to the presence of organization, while extremes can intensify faster in the aggregated state, leading to a faster amplification in the sporadic nature of rain. When convection aggregates, heavy rain is enhanced by 20%–30% and nonlinear behaviors are observed as a function of SST and strength of aggregation feedbacks. First, radiative- and surface-flux aggregation feedbacks have multiplicative effects on extremes, illustrating a non-trivial sensitivity to the degree of organization. Second, alternating Clausius-Clapeyron and super-Clausius-Clapeyron regimes in extreme rainfall are found as a function of SST, corresponding to varying thermodynamic and dynamic contributions, and a large sensitivity to precipitation efficiency variations in some SST ranges. The potential for mesoscale circulations in amplifying the hydrologic cycle is established. However, these nonlinear distortions question the quantitative relevance of idealized self-aggregation. This calls for a deeper investigation of relationships which capture the coupling between global energetics, aggregation feedbacks and local convection, and for systematic tests of their sensitivity to domain configurations, surface boundary conditions, microphysics, and turbulence schemes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Mechanisms of Projected Changes in Thunderstorm Downburst Environments Across the United States

Responses of downdraft convective available potential energy (DCAPE) to global warming were investigated using the Community Earth System Model (CESM2) under a high‐emission scenario through the year 2100. DCAPE is projected to increase by 5%–12% on average in most areas, independently of wind shear. A diagnostic of downdraft buoyancy is introduced to understand the mechanisms of DCAPE responses. Much of the increase in mean DCAPE is temperature‐driven, with additional contributions from changes in relative humidity and downdraft origin heights. However, extreme values increase at much faster rates than can be explained by local warming. In winter, the latitude of significant DCAPE and CAPE shifts poleward by more than 5° due to larger changes in downburst environments within midlatitude cyclones. The projected increase in cold‐season extremes indicates an interaction between weather events and warming trends that increases the potential for downbursts and straight‐line winds in winter.

Williams, Ian N. [Iowa State Univ., Ames, IA (Unit↗
DOE OSTI2023

World’s strongest laser enables pressure-driven ionization

The degree of ionization inside giant planets and stars determines their material properties. In burning stars, ionization is controlled by temperature, whereas pressure-driven ionization is dominant in cooler objects. Finally, experiments creating the extreme conditions needed for pressure-driven ionization in the laboratory shed light on this complex process.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Ligand-channel-enabled ultrafast Li-ion conduction

Li-ion batteries (LIBs) for electric vehicles and aviation demand high energy density, fast charging and a wide operating temperature range, which are virtually impossible because they require electrolytes to simultaneously have high ionic conductivity, low solvation energy and low melting point and form an anion-derived inorganic interphase. We report guidelines for designing such electrolytes by using small-sized solvents with low solvation energy. The tiny solvent in the secondary solvation sheath pulls out the Li + in the primary solvation sheath to form a fast ion-conduction ligand channel to enhance Li + transport, while the small-sized solvent with low solvation energy also allows the anion to enter the first Li + solvation shell to form an inorganic-rich interphase. The electrolyte-design concept is demonstrated by using fluoroacetonitrile (FAN) solvent. The electrolyte of 1.3 M lithium bis(fluorosulfonyl)imide (LiFSI) in FAN exhibits ultrahigh ionic conductivity of 40.3 mS cm -1 at 25 °C and 11.9 mS cm -1 even at -70 °C, thus enabling 4.5-V graphite||LiNi 0.8 Mn 0.1 Co 0.1 O 2 pouch cells (1.2 Ah, 2.85 mAh cm -2 ) to achieve high reversibility (0.62 Ah) when the cells are charged and discharged even at -65 °C. The electrolyte with small-sized solvents enables LIBs to simultaneously achieve high energy density, fast charging and a wide operating temperature range, which is unattainable for the current electrolyte design but is highly desired for extreme LIBs. This mechanism is generalizable and can be expanded to other metal-ion battery electrolytes.

25 ENERGY STORAGE↗