Search NASA⌕ Search

SEARCH · Search NASA

Results for “Space air temperature 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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Model-based predictive control of multi-stage air-source heat pumps integrated with phase change material-embedded ceilings

This paper presents a model-based predictive control strategy to optimize the operations of phase change material (PCM) ceiling panels coupled with a multi-stage air-source heat pump. A three-stage prototype heat pump unit has been built and tested in the laboratory, with the low and medium stages designed for space heating/cooling and the high compression stage dedicated to charging of the PCM energy storage. To facilitate optimal control of the integrated heat pump system, a mixed-integer linear programming formulation is derived through linearization of the heat pump model and a mixed-integer reformulation of the PCM dynamic governing equations. A predictive control strategy is synthesized based on the resultant control formulation and implemented in a receding horizon scheme that optimizes the PCM charging and the zone temperature schedules simultaneously to leverage both the passive (associated with building construction materials) and active (PCM) storage capacities of a building. The control strategy has been tested along with three benchmarking control scenarios using a co-simulation platform for a prototypical detached house in Atlanta, GA. In this study, test results showed that application of the proposed control strategy to the PCM-integrated heat pump could provide 27.1% electricity cost savings while a fine tuned rule-based control strategy could achieve cost savings of 20.4%, compared to a baseline case without PCM storage, under a time-of-use rate tariff.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Dynamic structural and microstructural responses of a metal–organic framework type material to carbon dioxide under dual gas flow and supercritical conditions

The structural and microstructural responses of a model metal–organic framework material, Ni(3-methyl-4,4'-bipyridine)[Ni(CN) 4 ] (Ni-BpyMe or PICNIC-21), to CO 2 adsorption and desorption are reported for in situ small-angle X-ray scattering and X-ray diffraction measurements under different gas pressure conditions for two technologically important cases. These conditions are single or dual gas flow (CO 2 with N 2 , CH 4 or H 2 at sub-critical CO 2 partial pressures and ambient temperatures) and supercritical CO 2 (with static pressures and temperatures adjusted to explore the gas, liquid and supercritical fluid regimes on the CO 2 phase diagram). The experimental results are compared with density functional theory calculations that seek to predict where CO 2 and other gas molecules are accommodated within the sorbent structure as a function of gas pressure conditions, and hence the degree of swelling and contraction in the associated structure spacings and void spaces. Furthermore, these predictions illustrate the insights that can be gained concerning how such sorbents can be designed or modified to optimize the desired gas sorption properties relevant to enhanced gas recovery or to addressing carbon dioxide reduction through carbon mitigation, or even direct air capture of CO 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2026

Itinerant Magnetism in Hydride-Synthesized CaCo 12 B 6

A new compound in the underexplored Ca–Co–B phase space has been discovered, validating high-throughput computations from the Open Quantum Materials Database, which predicted thermodynamic stability for CaCo 12 B 6 in the SrNi 12 B 6 structure type. The synthetic effects of different boron precursors and the advantages of using CaH 2 instead of Ca metal were demonstrated by the short synthesis duration and high purity of CaCo 12 B 6 , in contrast with traditional synthesis routes. Powder X-ray diffraction (PXRD) confirmed that CaCo 12 B 6 shares the SrNi 12 B 6 structure ( R $\bar{3}$m (#166), a = 9.469(4) Å, c = 7.468(2) Å, Z = 3) and is water- and air-stable. High-temperature in situ PXRD indicates that CaCo 12 B 6 is stable below 1050 K under vacuum in a silica capillary. CaCo 12 B 6 decomposes between 693 and 773 K during spark-plasma sintering. Density functional theory calculations indicate that CaCo 12 B 6 is metallic with a ferromagnetic ground state. X-ray absorption near-edge spectroscopy and Bader charge analysis indicate that Co atoms in CaCo 12 B 6 lack ionic character. Magnetometry reveals room-temperature paramagnetism with μ eff = 1.7(1)μ B per Co atom and a Weiss constant of +190(10)K. Ferromagnetic ordering occurs below 172(1)K, resulting in a saturation moment of 0.46 μ B per Co atom. Our findings demonstrate that the hydride route is a viable strategy for discovery of new ternary alkaline-earth-transition metal borides analogous to rare-earth-containing counterparts.

diffraction↗
DOE OSTI2020

Field-Scale Lysimeter Studies of Glass and Cementitious Waste Forms at the Hanford Site - 20392

The Hanford site Integrated Disposal Facility (IDF) will receive waste forms from vitrification activities at the Hanford Waste Treatment and Immobilization Plant (WTP). The waste form inventory to be disposed of at the IDF will consist of vitrified low-activity waste (LAW) in glass forms and solidified (or encapsulated) secondary wastes in cementitious forms. The IDF is a near-surface burial facility located near Hanford's Waste Treatment and Immobilization Plant in the 200 East Area of the site's Central Plateau. An extensive set of laboratory experimental data has been collected to support IDF performance assessment calculations of the eventual degradation of waste forms and mobility of contaminants. This paper describes the start of a field experiment to generate waste-form performance data on a larger scale (tens of centimeters), over a longer duration (five years or more), and under field conditions representative of the IDF. Results from this study are expected to improve model descriptions of contaminant mobility, reduce uncertainties about the representativeness of laboratory results in the IDF performance assessment, improve stakeholder confidence in the safe disposal of treated waste at the IDF, and facilitate the adoption of informed facility designs with the potential to reduce operational costs. A lysimeter test facility near Hanford's 200 West Area has been repurposed to carry out long-term assessments of waste forms buried in sediments excavated from the IDF. The waste forms are buried in large drainage lysimeters, open caissons that are two meters in diameter and three meters deep. Waste forms are buried in up to six locations in each lysimeter. Samplers collect pore water and drainage water beneath the waste forms and air from the pore space adjacent to waste forms. Sensors measure temperature, soil water content, soil water tension, and drainage flux. One lysimeter containing cementitious waste forms and one containing glass waste forms have been completed, along with a control lysimeter (without waste forms). The cementitious waste forms are Cast Stone grout formulations using a liquid secondary waste simulant and a generic Hanford high-salt simulant, as well as a hydrated lime-based grout formulation using a liquid secondary waste simulant. Technetium-99 and iodine-127 were added as tracers to monitor contaminant mobility. Glass waste forms were fabricated in two formulations (LAWA44 and ORLEC28), with rhenium and molybdenum tracers to monitor waste form degradation. The predicted performance of the waste forms in the lysimeters was modeled prior to installation to determine waste form size, tracer concentration/activity, and locations of sensors and samplers. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)

Abstract. Predicting future climate change over a region of complex terrain, such as the western United States (US), remains challenging due to the low resolution of global climate models (GCMs). Yet the climate extremes of recent years in this region, such as floods, wildfires, and drought, are likely to intensify further as climate warms, underscoring the need for high-quality and high-resolution predictions. Here, we present an ensemble of dynamically downscaled simulations over the western US from 1980–2100 at 9 km grid spacing, driven by 16 latest-generation GCMs. This dataset is titled the Western US Dynamically Downscaled Dataset (WUS-D3). We describe the challenges of producing WUS-D3, including GCM selection and technical issues, and we evaluate the simulations' realism by comparing historical results to temperature and precipitation observations. The future downscaled climate change signals are shaped in physically credible ways by the regional model's more realistic coastlines and topography. (1) The mean warming signals are heavily influenced by more realistic snowpack. (2) Mean precipitation changes are often consistent with wetting on the windward side of mountain complexes, as warmer, moister air masses are uplifted orographically during precipitation events. (3) There are large fractional precipitation increases on the lee side of mountain complexes, leading to potentially significant changes in water resources and ecology in these arid landscapes. (4) Increases in precipitation extremes are generally larger than in the GCMs, driven by locally intensified atmospheric updrafts tied to sharper, more realistic gradients in topography. (5) Changes in temperature extremes are different from what is expected by a shift in mean temperature and are shaped by local atmospheric dynamics and land surface feedbacks. Because of its high resolution, comprehensiveness, and representation of relevant physical processes, this dataset presents a unique opportunity to evaluate societally relevant future changes in western US climate.

Rahimi, Stefan (ORCID:0000000331884462)↗
DOE OSTI2026

Geothermal Heat Pump System Showcase: Short-Term Validation of Borehole Heat Exchanger Performance from Field Data to Numerical Modeling: Preprint

Since 2011, a geothermal heat pump (GHP) system has been operating to provide space heating and cooling for the Solar Radiation and Research Laboratory building at the National Laboratory of the Rockies (NLR) in Golden, Colorado. The system consists of 23 vertical boreholes, each extending to a depth of 300 ft (91 m), connected to 11 water-to-air heat pump units and four circulation pumps. Between fiscal years 2023 and 2025, additional power meters and temperature sensors were retrofitted to support detailed system performance assessment and model development. This study presents preliminary monitoring results and the development of an initial numerical model of the borehole heat exchanger field. The model incorporated site-specific geometry, ground thermal properties derived from thermal response tests, and ambient temperatures, and simulated system behavior over a representative operating day in September. Model predictions of outlet temperatures were compared against corresponding field measurements. Results showed that modeling initialized with a simplified linear subsurface temperature gradient presents systematic discrepancies in outlet temperature, whereas incorporating depth-resolved borehole temperature measurements for initialization yields substantially improved agreement with observations. The findings highlight the sensitivity of short-term predictive modeling to the representation of initial subsurface thermal conditions and underscore the value of high-resolution field measurements for model calibration and validation. These preliminary results inform ongoing efforts to extend the modeling framework to longer time horizons and to refine monitoring and modeling strategies that support the design guidance and operational optimization of GHP systems in research and commercial buildings.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Arctic Observing Experiment (AOX) Field Campaign Report

Our ability to understand and predict weather and climate requires an accurate observing network. One of the pillars of this network is the observation of the fundamental meteorological parameters: temperature, air pressure, and wind. We plan to assess our ability to measure these parameters for the polar regions during the Arctic Observing Experiment (AOX, Figure 1) to support the International Arctic Buoy Programme (IABP), the Arctic Observing Network (AON), the International Program for Antarctic Buoys (IPAB), and the Southern Ocean Observing System (SOOS). Accurate temperature measurements are also necessary to validate and improve satellite measurements of surface temperature across the Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Seamlessly Fuel Flexible Heat Pump with Optimal Model-based Control Strategies to Reduce Peak Demand, Utility Cost and CO2 Emission

This research develops a novel hybrid fuel heat pump system for space heating of residential and small commercial buildings with built-in optimization and control. Whereas conventional dual fuel systems either run on gas or electricity at any given moment, the proposed seamlessly fuel flexible heat pump (SFFHP) simultaneously consumes gas and electricity and continuously optimizes the proportion of each. The building air flows across the heat pump condenser first and then flows across the furnace coil, and this reduces the heat pump temperature lift. The SFFHP delivers energy savings by allowing each subsystem (gas furnace and electric heat pump) to operate where it performs best to improve energy efficiency, minimize energy cost, and minimize carbon footprint. The capacities of the electric heat pump and gas furnace are continuously adjusted based on ambient conditions, utility price signals, and marginal grid emission signals. An optimal model predictive control strategy was developed with the goal of minimizing utility cost and minimizing CO2 emission. Two case studies were conducted to simulate the performance of SFFHP during the heating season in Chicago and Los Angeles, respectively. Compared with a conventional electric heat pump, SFFHP yields 33% utility cost reduction and 49% CO2 emission reduction in Chicago. Similarly, it achieves 23% utility cost reduction and 17% CO2 emission reduction in Los Angeles. Case studies demonstrate that SFFHP can deliver significant reductions in peak demand, utility cost, and CO2 emission. Due to the hybrid fuel nature of this novel equipment, user comfort will always be maintained. The fuel flexibility makes it an attractive option for demand response programs.

Li, Zhenning↗
DOE OSTI2020

Prediction of annual soil respiration from its flux at mean annual temperature

Accurately scaling soil respiration (SR, the soil-to-atmosphere flow of CO2) across time and space is important to constrain and understand ecosystem to global scale SR, a major terrestrial carbon flux to the atmosphere. Year-round SR measurements are however expensive and sometimes impossible to perform. Bahn et al. (2010) developed an approach to estimate annual SR (SRannual) from the flux measured at mean soil temperature (SRMAST), but the robustness of this approach needs to be evaluated in diverse ecosystem types and climatic conditions globally. We used a global soil respiration database (SRDB-V4, with 823 SR observations worldwide) to test the capability of SRMAST to predict SRannual. SRMAST estimated using a variety of methods all showed clear relationships with annual SRannual. Two single-rate methods (i.e., using the single SR rate most close to mean annual soil temperature, or the single SR rate most close to mean annual air temperature) showed the most pronounced divergence from the true SRannual, but errors significantly decreased when using multiple SR rates within 1 ? of the mean annual soil temperature to estimate SRMAST. SRannual was most closely correlated with SRMAST estimated via a Q10 relationship, but this method has a potential autocorrelation issue that we explore and discuss. Air temperature data are much more widely available than is soil temperature, and we found that SR at mean annual air temperature (SRMAAT) can be used to predict SRannual as well. This study builds on Bahn et al. (2010) to demonstrate that SR measured at both annual mean soil and air temperature can be used to predict annual SR, with well-quantified errors. This capability could be used to reduce SR measurement frequency required for estimating SRannual and greatly decrease cost, factors that are generally important but especially in lower-income countries and cold, inaccessible regions.

Soil respiration, temperature, modeling↗
DOE OSTI2022

How will United States commercial building energy use be impacted by IPCC climate scenarios?

Climate change and anthropogenically-forced shift of weather in the future will impact energy use and resilience of both the built environment and the electric grid. The aim of this analysis is to understand how future climate scenarios will impact electricity and natural gas use of commercial buildings in the United States. Here, this study analyzes this impact for 2030, 2045, and 2100 using Representative Concentration Pathways (RCP) scenarios defined in Intergovernmental Panel on Climate Change (IPCC) Assessment Report 5. The large, gridded simulation of meteorological variables for RCPs 2.6, 4.5, 6.0, and 8.5 are selected and downscaled to make available hourly Future Meteorological Year (FMY) weather files for use and improvement in subsequent studies. High performance computing resources use these FMYs to simulate commercial prototype buildings in every American Society of Heating, Refrigeration, and Air Conditioning Engineers (ASHRAE) climate zone of the United States (US), and results are scaled to nation-wide energy use using conditioned floor area multipliers. The analysis is conducted without speculating the physical and performance traits of future buildings or the grid characteristics. This analysis quantifies the impact of climate change on source electrical and natural gas usage for commercial buildings in the United States over the next 80 years. If US commercial floorspace remained constant, total energy use by 2100 is predicted between an 1.75% decrease under the greatest emission scenario (8.5) and a 1.76% increase under the lowest emission scenario (2.6). When adjusted for anticipated urban growth by 2100, the predicted range is 65% increase (8.5) and 71% increase (2.6). Under a global temperature rise climate scenario, the warmest US climate zones will see a large increases in electricity use derived from space cooling while the coldest US climate zones will see significant decreases in natural gas use caused by the decrease in heating necessary. While climate change may ultimately require adaptations of the built environment to withstand its effects and because the United States is a country that requires more heating than cooling, from a building energy perspective, climate change (average temperature rise) is a net energy saver for the United States.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Quasi‐Binary Transition Metal Dichalcogenide Alloys: Thermodynamic Stability Prediction, Scalable Synthesis, and Application

Abstract Transition metal dichalcogenide (TMDCs) alloys could have a wide range of physical and chemical properties, ranging from charge density waves to superconductivity and electrochemical activities. While many exciting behaviors of unary TMDCs have been demonstrated, the vast compositional space of TMDC alloys has remained largely unexplored due to the lack of understanding regarding their stability when accommodating different cations or chalcogens in a single‐phase. Here, a theory‐guided synthesis approach is reported to achieve unexplored quasi‐binary TMDC alloys through computationally predicted stability maps. Equilibrium temperature–composition phase diagrams using first‐principles calculations are generated to identify the stability of 25 quasi‐binary TMDC alloys, including some involving non‐isovalent cations and are verified experimentally through the synthesis of a subset of 12 predicted alloys using a scalable chemical vapor transport method. It is demonstrated that the synthesized alloys can be exfoliated into 2D structures, and some of them exhibit: i) outstanding thermal stability tested up to 1230 K, ii) exceptionally high electrochemical activity for the CO 2 reduction reaction in a kinetically limited regime with near zero overpotential for CO formation, iii) excellent energy efficiency in a high rate Li–air battery, and iv) high break‐down current density for interconnect applications. This framework can be extended to accelerate the discovery of other TMDC alloys for various applications.

Hemmat, Zahra↗
DOE OSTI2025

CareWELL: Multimodal Region Representation Learning with Spatial Contexts for Urban Health

Rapid urbanization affects living environments by intensifying exposure to air pollution, heat, noise, and urban dynamics, which together contribute to uneven health outcomes across neighborhoods. For instance, cardiovascular, respiratory, and mental health conditions are each influenced by distinct exposures such as air pollution, extreme temperatures, or limited access to green space. These heterogeneous patterns require understanding the characteristics of geographic regions in order to explain why urban health risks vary across urban areas. Recent work in self-supervised region representation learning provides a promising way to model such characteristics from multimodal geospatial data. However, existing methods face two major limitations: (i) they often depend on non-public datasets, limiting reproducibility and applicability, and (ii) their generic pretraining objectives overlook health-relevant determinants, including temporal variability in environmental exposures and inequalities in social conditions. To address these gaps, we propose Context-Aware Region rEpresentation with Weather, Environment, and Location Learning (CareWELL). CareWELL leverages large language models to encode seasonal variability in weather, employs contrastive learning to align geo-coordinate and weather representations, and introduces a context-aware objective that integrates socio-demographic factors while preserving spatial correlations. We evaluate CareWELL by predicting six urban health outcomes in Manhattan, New York City, and demonstrate that CareWELL consistently outperforms state-of-the-art baselines as well as a traditional spatial computing method. These results suggest the importance of context-aware pretraining objectives for learning health-relevant region representations.

Namgung, Min [ORNL]↗
DOE OSTI2023

Effects of additively manufactured surface roughness on small diameter plenums with multiple side discharges for high temperature gas turbine blade cooling applications

Combined heat and power (CHP) applications have significant environmental and economic benefits that are consistent with the goals of the U.S. Department of Energy (DOE). One area that is currently being studied includes the potential benefits of CHP turbine operation at higher turbine inlet temperatures. Internal cooling concepts enabled by additive manufacturing (AM) are of primary interest. Here, the effectiveness of internal cooling is hindered by many factors such as velocity distribution of the cooling air to the hot surface considering impingement cooling. To simulate cooling air exiting from a series of orifices for internal cooling in an airfoil, a straight smooth wall tubing with multiple side discharging orifices is used and compared to additively manufactured tubing (Ti6Al4V Grade 23) with orifice size and spacing as well as inner and outer diameters identical to the smooth wall tubing. Similar to flow discharging form perforated pipes, the flow discharged from individual orifices along the tubes in this study is found to be nonuniformly distributed, and the horizontal (axial direction) momentum can be observed from the experimental data. Discharge velocities have been measured with two-dimensional (2D) particle imaging velocimetry (PIV) and single element hot wire anemometry. Numerical analysis has also been conducted to predict the velocity distributions along the orifices in the smooth wall and additive manufacturing (AM) tubing, which are inherited with surface roughness. Numerical and measured results in this study are compared, presented, and discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Event-Based Energy Impact Tracking and Forecasting with Limited Measurements for Rooftop Units

Packaged air conditioning units and heat pumps, also known as rooftop units (RTUs), are responsible for almost 133 billion kWh of electricity usage annually on site for space cooling U.S. commercial buildings. In addition, the use of heat pumps is a trend we expect to accelerate as buildings transition from fossil fuel-based heating to electricity as a key step for decarbonizing the U.S. commercial buildings sector. However, the operation conditions and energy use of RTUs and heat pumps are usually not well monitored as they are not commonly integrated with building automation systems and lack exposed sensing and control points. To fill this gap, this paper proposes a framework for tracking and forecasting energy impacts resulting from degradation of performance and improved performance for unit servicing using limited data. The proposed framework makes use of a constrained dataset, specifically measurements of the outdoor air temperature and the power demand of individual RTUs, to track and forecast changes in energy use associated with changes in performance over various temporal horizons ranging from days to weeks. Following the detection of an RTU fault, performance degradation, or performance improvement, the framework employs a prediction model to assess the cumulative energy impact. We demonstrate the effectiveness of the method with field-collected data for servicing and degradation examples and compare the predicting accuracy of Gradient Boosting Decision Tree (GBDT) Regression models to Support Vector Regression and Linear Regression models. The results show that GBDT achieved the best accuracy for time-series validation datasets for the servicing and degradation cases, and the prediction model was able to track the cumulative energy impacts of events. The proposed framework can inform building owners of the cumulative change in energy usage of RTUs associated with performance degradation, performance improvement, or a fault.

packaged air conditioners, packaged heat pumps, ro↗
DOE OSTI2022

Hybrid Heat Pump Controls: Conventional Dual Fuel versus Seamlessly Fuel Flexible Heat Pump

This paper compares the performance of a novel seamlessly fuel flexible heat pump (SFFHP) and conventional dual fuel heat pump (DFHP) for space heating. The conventional dual fuel systems either run on the gas furnace or electric heat pump at any given moment, as a comparison, the proposed seamlessly fuel flexible heat pump simultaneously consumes gas and electricity by continuously optimizing the proportion of each. The process air flows across the heat pump condenser first and then flows across the furnace coil, therefore, the heat pump temperature lift is reduced. SFFHP delivers energy savings by allowing each subsystem, i.e., gas furnace and electric heat pump, to operate where it performs best.For DFHP, two operation control strategies, i.e., non-restricted control and restricted control, are available on market. For the non-restricted mode, the thermostat has a switching temperature-programmed according to the balancing point of heating load and capacity curve. Heat pump operates above the switching temperature, while the furnace takes over under the switching temperature. For the restricted control, the compressor of a heat pump is disabled below a predefined lockout outdoor temperature to let the furnace take over. For SFFHP, a model predictive control strategy is developed to continuously adjust the capacities of the electric heat pump and gas furnace based on the foreseen weather data, utility price signals, and marginal grid emission signals with the goal of minimizing the utility cost and CO2 emission while guaranteeing comfort requirements.In this paper, DFHP and SFFHP are simulated using high-fidelity heat pump performance curves generated from DOE/ORNL heat pump design model. Performance comparison of DFHP and SFFHP during 2019-2020 heating season in Los Angeles shows that SFFHP with model predictive control achieves 23% utility cost reduction and 17 % CO2 emission reduction. Case studies demonstrate that SFFHP can deliver significant reductions in peak demand, utility cost, and CO2 emission. As a result, SFFHP can deliver superior benefits for utility cost reduction and CO2 emission reduction over conventional dual fuel heat pump.

Li, Zhenning↗
DOE OSTI2026

Enhancing photoionization rate calculations in low-temperature plasmas using spectral methods

Photoionization plays a central role in the development of streamer discharges and other non-equilibrium plasma phenomena. It creates seed electrons, which are essential for positive streamer propagation, allowing the ionization front to move forward. Because of this, accurate modeling of photoionization is very important for predicting streamer behavior and plasma evolution. The photoionization process in air (N 2 – O 2 mixture) is often described by the Zheleznyak model (1982). This model is usually solved through Helmholtz-type equations that approximate the Zheleznyak photoionization model (Zheleznyak et al. 1982) as Partial Differential Equations (PDEs). Conventional numerical methods, such as the Finite Difference Method (FDM) or Finite Volume Method (FVM), are widely used to solve these equations. Although they are prevalent, the computational cost of these methods due to their need for matrix operations and iterative solver is demanding. To address this challenge, this work develops a spectral solver based on the Fast Fourier Transform (FFT) combined with Discrete Cosine Transform (DCT) and Discrete Sine Transform (DST) to calculate the photoionization rate efficiently in an axisymmetric cylindrical domain. This method naturally satisfies the boundary conditions used in the model and converts the PDE into algebraic ones in spectral space. Thus, avoids the need for iterative matrix solvers. When compared with FDM results, it is demonstrated that the new solver not only maintains accuracy, but also reduces the computational cost, showing a performance increase of approximately 100 compared to FDM over a wide range of problem sizes. The method is parallelized using Message Passing Interface (MPI) and has been integrated into a fluid plasma model for streamer simulation. Here, this FFT-based approach provides a fast and reliable alternative for calculating photoionization in fluid models, helping large-scale plasma simulations run faster and efficiently, and allows higher-resolution simulation without extra computational cost.

Axisymmetric system↗
DOE OSTI2022

Information Content of a Synergy of Ground-Based and Space-Based Infrared Sounders. Part I: Clear-Sky Environments

Abstract Profiles of atmospheric temperature and water vapor from remotely sensed platforms provide critical observations within the temporal and spatial gaps of the radiosonde network. The 2017 National Academies of Science Decadal Survey highlighted that observations of the planetary boundary layer (PBL) from the current space-based observing system are not of the necessary accuracy or resolution for monitoring and predicting high-impact weather phenomena. One possible solution to improving observations of the PBL is supplementing the existing space-based observing system with a network of ground-based profilers. A synthetic information content study is developed utilizing profiles from the Atmospheric Radiation Measurement (ARM) program sites at the Southern Great Plains (SGP), east North Atlantic (ENA), and North Slope of Alaska (NSA) to assess the benefits, in terms of degrees of freedom (DOF), vertical resolution, and uncertainties, of a synergy between the ground-based Atmospheric Emitted Radiance Interferometer (AERI) with space-based hyperspectral infrared (IR) sounders. A combination of AERI with any of the three polar-orbiting IR sounders: the Atmospheric Infrared Sounder (AIRS), the Cross-track Infrared Sounder (CrIS), or the Infrared Atmospheric Sounding Interferometer (IASI), results in a DOF increase of 30%–40% in the surface-to-700-hPa layer compared to the space-based instrument alone. Introducing AERI measurements to the observing system also results in significant improvements to vertical resolution and uncertainties in the bottom 1000 m of the atmosphere compared to CrIS measurements alone. A synergy of CrIS and AERI exceeds the 1-km-vertical-resolution goal set by the Decadal Survey in the lowest 1000 m.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Impact of titanium content on the thermo-mechanical and oxidation response of TiAlTa

This study aimed to analyze how the addition of titanium (Ti) to TiAlTa alloys affects their mechanical properties (Young’s modulus and hardness) and oxidation behavior. Alloys with three different Ti additions and equi-atomic Al and Ta were fabricated with nominal compositions of 33Ti-33Al-33Ta at%, 50Ti-25Al-25Ta at%, and 70Ti-15Al-15Ta at%. Phase identification of as-processed and compositionally homogenized alloys was conducted by coupling various electron microscopy, diffraction, and chemical analysis techniques. Composition and structures were modeled using CALPHAD-based phase predictions and compared with experimental results. Each of the alloys exhibited a unique set of microstructures with distinctly different ordered precipitates, dependent on cooling rate and chemical composition. Subsequently, nanoindentation tests were performed at temperatures of 25°C, 250°C, 500°C, and 750°C. Oxidation studies were conducted under static air at 750°C for up to 200 h. 33Ti-33Al-33Ta at% and 70Ti-15Al-15Ta at% alloys showed higher hardness and modulus than 50Ti-25Al-25Ta at% at room temperature. The 50Ti-25Al-25Ta at% alloy exhibited higher hardness and modulus values but lower oxidation resistance at 750°C when compared with the other specimens. The X-ray photoelectron spectroscopy experiments were conducted to further analyze the oxides present in the samples. Despite each sample displaying combinations of mixed oxide layers, TiO 2 was the preferred oxide forming in the 50Ti-25Al-25Ta composition, while the other samples preferred to form Al 2 O 3 . In conclusion, the findings from this systematic exploration of phase evolution in the TiAlTa alloy space provide insights for optimized material chemistries, processing, and properties.

36 MATERIALS SCIENCE↗