Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “cold cloud”

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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Wintertime synoptic patterns of midlatitude boundary layer clouds over the western North Atlantic: Climatology and insights from in-situ ACTIVATE observations

The winter synoptic evolution of the western North Atlantic and its influence on the atmospheric boundary layer is described by means of a regime classification based on Self Organizing Maps applied to 12 year of data (2009-2020). The regimes are classified into categories according to daily 600-hPa geopotential height: dominant ridge, trough to ridge eastward transition (trough-ridge), dominant trough, and ridge to trough eastward transition (ridge-trough). A fifth synoptic regime resembles the winter climatological mean. Coherent changes in sea-level pressure and large-scale winds are in concert with the synoptic regimes: 1) the ridge regime is associated with a well-developed anticyclone; 2) the trough-ridge gives rise to a low pressure center over the ocean, ascents, and northerly winds over the coastal zone; 3) trough is associated with the eastward displacement of a cyclone, coastal subsidence, and northerly winds, all representative characteristics of cold-air outbreaks; 4) the ridge-trough regime features the development of an anticyclone and weak coastal winds. Low clouds are characteristic of the trough regime, with both trough and trough-ridge featuring synoptic maxima in cloud droplet number concentration (N d ). The N d increase is primarily observed near the coast, concomitant with strong surface heat fluxes exceeding by more than 400 W m -2 compared to fluxes further east. Five consecutive days of aircraft observations collected during the ACTIVATE campaign corroborates the climatological characterization, confirming the occurrence of high N d for days identified as trough. This study emphasizes the role of boundary-layer dynamics and aerosol activation and their roles in modulating cloud microphysics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Realism of Lagrangian Large Eddy Simulations Driven by Reanalysis Meteorology: Tracking a Pocket of Open Cells Under a Biomass Burning Aerosol Layer

An approach to drive Lagrangian large eddy simulation (LES) of boundary layer clouds with reanalysis data is presented and evaluated using satellite (Spinning Enhanced Visible and Infrared Imager, SEVIRI) and aircraft (Cloud-Aerosol-Radiation Interactions and Forcing, CLARIFY) measurements. The simulations follow trajectories of the boundary layer flow. They track the formation and evolution of a pocket of open cells (POC) underneath a biomass burning aerosol layer in the free troposphere. The simulations reproduce the evolution of observed stratocumulus cloud morphology, cloud optical depth, and cloud drop effective radius, and capture the timing of the cloud state transition from closed to open cells seen in the satellite imagery on the three considered trajectories. They reproduce a biomass burning aerosol layer identified by the in-situ aircraft measurements above the inversion of the POC. Entrainment of aerosol from the biomass burning layer into the POC is limited to the extent of having no impact on cloud- or boundary layer properties, in agreement with the CLARIFY observations. The two-moment bin microphysics scheme used in the simulations reproduces the in-situ cloud microphysical properties reasonably well. A two-moment bulk microphysics scheme reproduces the satellite observations in the non-precipitating closed-cell state, but overestimates liquid water path and cloud optical depth in the precipitating open-cell state due to insufficient surface precipitation. A boundary layer cold and dry bias occurring in LES can be counteracted by reducing the grid aspect ratio and by tightening the large scale wind speed nudging towards the surface.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Bottom-up Approach to Improve the Representation of Deep Convective Clouds in Weather and Climate Models (Final Report)

A fundamental yet outstanding question about deep cumulus convection regards how convective updrafts, downdrafts, and surface-based cold pools are inter-related within organized storms, and how these three convective components are modulated by external and internal factors. We considered this question through numerical model simulations as well as data collected during the MC3E field campaign. One of our basic hypotheses was that deep cold pools are forced by wide downdrafts which arise from wide updrafts. This “bottom-up” perspective required consideration of the external controls on updraft width, and then the internal controls on cold-pool characteristics including depth. Model experiments showed that environmental vertical wind shear (an external factor) exerts a particularly strong control on updraft width; analyses of linear and nonlinear dynamic pressure forcing readily explain this control. The experiments also showed that increases in updraft width are accompanied by corresponding increases in downdraft width and cold-pool depth. The updraft–downdraft connection is through precipitation: the wide area of precipitation that will be initiated in a wide updraft will in turn lead to a wide downdraft. The downdraft–cold pool connection is through mass continuity: at the downdraft terminus, the large downdraft mass flux through a wide downdraft must lead to a deep cold pool. Model experiments also showed that the cold-pool depth and other characteristics can be significantly modulated by microphysical processes (internal factors). Specifically, the cold-pool expansion rate, depth, and intensity was found to depend most strongly on the amount of rain evaporation near the ground. However, the sustenance of the cold pool itself depended upon the downdrafts strengthened by sublimation of graupel higher in the storm. Finally, field campaign data revealed compelling inter-relationships between the cold-pool characteristics, and downdraft transience in terms of the microphysics. For example, pulses of hail and graupel (also internal factors) within downdrafts resulted in short-lived increases in the cold-pool depth. However, the cold-pool speed appeared to be relatively independent of the cold-pool depth and intensity, suggesting limitations of density current theory to convective cold pools in nature.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Thermodynamic Cloud Phase Classifications Using Machine Learning at NSA and ANX

Vertically resolved thermodynamic cloud phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) THERMOCLDPHASE Value-Added Product (VAP) uses a multi-sensor approach to classify thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave radiometer-derived liquid water path, and radiosonde temperature measurements. The measured voxels are classified as ice, snow, mixed-phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multilayer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with one year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1-score, and mean Intersection over Union (IOU). Analysis of ML confidence scores shows ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential datastreams for ML thermodynamic cloud phase predictions. The ML models’ generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. Finally, we evaluate the ML models’ response to simulated instrument outages and signal degradation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Demonstration of a MOT in a sub-millimeter membrane hole

Abstract We demonstrate the generation of a cold-atom ensemble within a sub-millimeter diameter hole in a transparent membrane, a so-called “membrane MOT”. With a sub-Doppler cooling process, the atoms trapped by the membrane MOT are cooled down to 10 $$\upmu$$ μ K. The atom number inside the unbridged/bridged membrane hole is about $$10^4$$ 10 4 to $$10^5$$ 10 5 , and the $$1/e^2$$ 1 / e 2 -diameter of the MOT cloud is about 180 $$\upmu$$ μ m for a 400 $$\upmu$$ μ m-diameter membrane hole. Such a membrane device can, in principle, efficiently load cold atoms into the evanescent-field optical trap generated by the suspended membrane waveguide for strong atom-light interaction and provide the capability of sufficient heat dissipation at the waveguide. This represents a key step toward the photonic atom trap integrated platform (ATIP).

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Quantifying the impacts of atmospheric rivers on the surface energy budget of the Arctic based on reanalysis

We present a comprehensive analysis of Arctic surface energy budget (SEB) components during atmospheric river (AR) events identified by integrated water vapor transport exceeding the monthly 85th-percentile climatological threshold in 3-hourly ERA5 reanalysis data from January 1980 to December 2019. Analysis of average anomalies in SEB components, net SEB, and the overall AR contribution to both the seasonal SEB components and net SEB climatology reveals clear seasonality and distinct land–sea–sea ice contrast patterns. Over the sea-ice-covered central Arctic Ocean, ARs significantly impact net SEB, inducing substantial surface warming in fall, winter, and spring. This warming is primarily driven by large anomalies in surface downward longwave radiation (LWD), which average 29–45 W m −2 during the cold seasons. In contrast, AR-related LWD anomalies are smaller in summer, averaging around 15 W m −2 , indicating a reduced impact during this season. Over sub-polar oceans, ARs have the most substantial positive impact on net SEB in cold seasons, mainly attributed to significant positive turbulent heat flux anomalies. AR-related turbulent heat anomalies reduce the upward turbulent flux, contributing up to −11 % relative to its seasonal climatology. In summer, ARs induce negative impacts on net SEB, primarily due to reduced shortwave radiation from increased cloud cover during AR events. Over continents, ARs generate smaller absolute impacts on net SEB because the large LWD anomalies are largely offset by corresponding increases in upward longwave radiation, particularly during cold seasons. Additionally, the seemingly large relative contributions of ARs to the net SEB over land primarily reflects the small magnitude of the climatological net SEB over continents. Greenland, especially western Greenland, exhibits significant downward longwave radiation anomalies associated with ARs, which drive large net SEB anomalies and contribute >54 % to mean SEB and induce amplified surface warming year-round. This holds significance for melt events, particularly during summer. Additionally, results of AR-related SEB impacts strongly depend on detection methods, as restrictive AR detection algorithms that emphasize extreme AR events, with large AR-related anomalies, do not necessarily indicate a large overall contribution to the SEB climatology due to the low occurrence frequency of these events. This study quantifies the role of ARs in the surface energy budget, contributing to our understanding of the Arctic warming and sea ice decline in ongoing Arctic amplification.

Arctic Sea ice change↗
DOE OSTI2024

Detecting rare neutral atomic-carbon absorbers with a deep neural network

ABSTRACT C i absorbers play an important role as indicators for exploring the presence of cold gas in the interstellar medium of galaxies. However, the current data base of C i absorbers is very limited due to their weak absorption feature and rarity. Here, we report results from a search of C i λλ1560, 1656 absorption lines using Mg ii absorbers as signposts with modified deep learning algorithms, which provides a very quick way to search for weak C i absorber candidates. A total of 107 C i absorbers were detected, which nearly doubles the size of previously known samples. In addition, we found 17 C i absorbers to be associated with 2175 Å dust absorbers (2DAs), i.e. about 16 per cent C i absorbers are associated with 2DAs. Comparing the average dust depletion patterns of C i absorbers with those of damped Lyman α absorbers (DLAs), Mg ii absorbers, Ca ii absorbers, and 2175 Å dust absorbers (2DAs) shows that C i absorbers generally have environments with more dust than DLAs, Mg ii, and Ca ii absorbers, but similar to dust in 2DAs. Similarity between the dust depletion pattern of C i absorbers to that of the warm disc in the Milky Way indicates that C i absorption clouds are possibly associated with disc components in distant galaxies. Therefore, C i absorbers are confirmed to be excellent probes to trace cold gas and dust in the Universe.

Ge, Jian↗
DOE OSTI2021

The Impact of Slantwise Descending Dry Intrusions on the Marine Boundary Layer and Air-Sea Interface Over the ARM Eastern North Atlantic Site

Dry intrusions (DIs) are synoptic-scale slantwise descending airstreams from the midlatitude upper troposphere toward the boundary layer at lower latitudes. Typically occurring behind cold fronts, such intrusions of dry air often reach the boundary layer and cause its deepening, thereby affecting boundary-layer clouds. Although subsidence is generally an inherent feature of the subtropical marine boundary layer (MBL), it is unclear how the MBL reacts to the transient, dynamically distinct DI. In this study, reanalysis data were combined with observations from the Atmospheric Radiation Measurement Eastern North Atlantic (ENA) site (39.1 degrees N,28.0 degrees W) to characterize the impact of DIs on MBL characteristics and clouds. Specifically, an objective criterion is applied to the observations made during the winter months of 2016-2018 to identify the DI days from those before and following DIs, and reference periods without DIs. The analyses suggest substantial deepening of the well-mixed boundary layer accompanied by changes in the cloud, precipitation and thermodynamic properties during the DI events. During the DI, the lower troposphere cooled and dried substantially thereby inducing strong surface sensible and latent heat fluxes. All while a strong inversion builds up at the elevated MBL top affecting cloud occurrence. The results show DIs to affect the boundary layer and cloud structure at the ENA site similar to 21% of the time in winter months, with the response of the cloud fields to the DI-fronts substantially different than that to the non-DI fronts. Hence, the DI events should be considered while studying boundary layer and cloud processes in the region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

E3SM‐Arctic: Regionally Refined Coupled Model for Advanced Understanding of Arctic Systems Interactions

Earth system models are essential tools for climate projections, but coarse resolutions limit regional accuracy, especially in the Arctic. Regionally refined meshes (RRMs) enhance resolution in key areas while maintaining computational efficiency. This paper provides an overview of the United States (U.S.) Department of Energy's (DOE's) Energy Exascale Earth System Model version 2.1 with an Arctic RRM, hereafter referred to as E3SMv2.1-Arctic, for the atmosphere (25 km), land (25 km), and ocean/ice (10 km) components. We evaluate the atmospheric component and its interactions with land, ocean, and cryosphere by comparing the RRM (E3SM2.1-Arctic) historical simulations (1950–2014) with the uniform low-resolution (LR) counterpart, reanalysis products, and observational data sets. The RRM generally reduces biases in the LR model, improving simulations of Arctic large-scale mean fields, such as precipitation, atmospheric circulation, clouds, atmospheric river frequency, and sea ice thickness. However, it introduces a seasonally dependent surface air temperature bias, reducing the LR cold bias in summer but enhancing the LR warm bias in winter, which contributes to the underestimated winter sea ice area and volume. Radiative feedback analysis shows similar climate feedback strengths in both model configurations, with the RRM exhibiting a more positive surface albedo feedback and contributing to a stronger surface warming than LR. These findings underscore the importance of high-resolution modeling for advancing our understanding of Arctic climate changes and their broader global impacts, although some persistent biases appear to be independent of model resolution at 10–100 km scales.

Energy Exascale Earth System Model (E3SM)↗
DOE OSTI2023

Analysis of an Arctic cold air outbreak during autumn and related air mass transformations forced by surface changes and advection in higher altitudes

During marine cold air outbreaks (MCAOs), cold and dry Arctic air masses are transported from the central Arctic southward across the closed sea ice and much warmer open oceans. They experience significant transformations including a rapid heating and moistening, often leading to cloud formation. While intense wintertime MCAOs have been analyzed widely, the air mass transformations during other seasons have been studied sparsely. We address this gap by investigating an MCAO case observed in September 2020. To study the transformation processes, we combine the fifth generation of atmospheric reanalyses of the global climate (ERA5), trajectory calculations, as well as shipborne and airborne measurements. In the central Arctic, observations acquired from aboard the research vessel (RV) Polarstern during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition characterized the initial state of the air mass over closed sea ice. Trajectories indicated the pathway the air mass took from RV Polarstern southward to the Fram Strait. For the first 24 h of the southbound drift, the air masses remained quasi-stationary. Then, still 15 h ahead of the marginal sea ice zone, differential advection across the boundary layer flow introduced humidity and clouds at higher altitudes between 1.5 and 2.5 km. ERA5-derived temperature and humidity tendencies indicated complex vertical interactions. Radiative cloud-top cooling, entrainment, and turbulence were significantly reduced in the lower and enhanced in the upper advected cloud layer. Eventually, the lower cloud deck dissipated. After this confluence of 2 different air masses, observations gathered by Polar 5 in Fram Strait as part of the MOSAiC Airborne observations in the Central Arctic campaign revealed cloudy, moist layers throughout the lowest 3.5 km and an increasing boundary layer height. Comparing the initial with the final state 48 h later, the largest net heating of +8 K was found close to the surface, yet the largest net moistening of +2.5 g kg -1 at an altitude of 1 km, as the initial profile was exceptionally dry here. We conclude that the observed air mass transformations were driven by the surface changes from sea ice to open ocean but additionally strongly impacted by the differential advection of clouds and moisture across the near-surface MCAO flow.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Development of a Full-Scale Connected U-Net for Reflectivity Inpainting in Spaceborne Radar Blind Zones

CloudSat’s Cloud Profiling Radar is a valuable tool for remotely monitoring high-latitude snowfall, but its ability to observe hydrometeor activity near the Earth’s surface is limited by a radar blind zone caused by ground clutter contamination. This study presents the development of a deeply supervised U-Net-style convolutional neural network to predict cold season reflectivity profiles within the blind zone at two Arctic locations. The network learns to predict the presence and intensity of near-surface hydrometeors by coupling latent features encoded in blind zone-aloft clouds with additional context from collocated atmospheric state variables (i.e., temperature, specific humidity, and wind speed). Results show that the U-Net predictions outperform traditional linear extrapolation methods, with low mean absolute error, a 38% higher Sørensen–Dice coefficient, and vertical reflectivity distributions 60% closer to observed values. The U-Net is also able to detect the presence of near-surface cloud with a critical success index (CSI) of 72% and cases of shallow cumuliform snowfall and virga with 18% higher CSI values compared to linear methods. An explainability analysis shows that reflectivity information throughout the scene, especially at cloud edges and at the 1.2-km blind zone threshold, along with atmospheric state variables near the tropopause, are the most significant contributors to model skill. This surface-trained generative inpainting technique has the potential to enhance current and future remote sensing precipitation missions by providing a better understanding of the nonlinear relationship between blind zone reflectivity values and the surrounding atmospheric state.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Factors Controlling Precipitation Onset and Maintenance: Inferences From Large Eddy Simulations of Two Afternoon Deep Convective Regimes Over Amazon

To investigate the environmental factors controlling the onset and maintenance of afternoon precipitation over tropical rainforests, two contrasting cases are created for large eddy simulations (LES) using GoAmazon observations: one features a single-pulse rain dissipating quickly in earlier afternoon, while the other shows double pulses lasting until evening. For these two specific cases under consideration, LES confirms that early-morning relative humidity dominates afternoon rain patterns. The attributed impacts are distinct: moisture determines the rain onset timing while temperature affects the peak rain intensity. Single-pulse day observes one round of strong precipitation and cold pools, which further suppresses convection. On double-pulse day, the first precipitation peak results from an intermediate development of congestus clouds, whose detrainment leads to a gradual moistening of the lower-to-middle troposphere. This behavior of convection favors a second pulse of stronger precipitation with more convective organization, whose development decouples from surface fluxes and sustains until evening.

Amazon↗
DOE OSTI2022

Cosmic rays in molecular clouds probed by H 2 rovibrational lines

Context. Low-energy cosmic rays (<1 TeV) play a fundamental role in the chemical and dynamical evolution of molecular clouds, as they control the ionisation, dissociation, and excitation of H 2 . Their characterisation is therefore important both for the interpretation of observations and for the development of theoretical models. However, the methods used so far for estimating the cosmic-ray ionisation rate in molecular clouds have several limitations due to uncertainties in the adopted chemical networks. Aims. Here, we refine and extend a previously proposed method to estimate the cosmic-ray ionisation rate in molecular clouds by observing rovibrational transitions of H 2 at near-infrared wavelengths, which are mainly excited by secondary cosmic-ray electrons. Methods. Combining models of interstellar cosmic-ray propagation and attenuation in molecular clouds with the rigorous calculation of the expected secondary electron spectrum and updated electron-H 2 excitation cross sections, we derive the intensity of the four H 2 rovibrational transitions observable in cold dense gas: (1—0)O(2), (1—0)Q(2), (1—0)S(0), and (1—0)O(4). Results. The proposed method allows the estimation of the cosmic-ray ionisation rate for a given observed line intensity and H 2 column density. We are also able to deduce the shape of the low-energy cosmic-ray proton spectrum impinging upon the molecular cloud. In addition, we present a look-up plot and a web-based application that can be used to constrain the low-energy spectral slope of the interstellar cosmic-ray proton spectrum. We finally comment on the capability of the James Webb Space Telescope to detect these near-infrared H 2 lines, which will make it possible to derive, for the first time, spatial variation in the cosmic-ray ionisation rate in dense gas. Besides the implications for the interpretation of the chemical-dynamic evolution of a molecular cloud, it will finally be possible to test competing models of cosmic-ray propagation and attenuation in the interstellar medium, as well as compare cosmic-ray spectra in different Galactic regions

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Combined Cycle Integrated Thermal Energy Storage “CiTES” (Final Scientific/Technical Report)

The Phase I of this project confirmed the technical feasibility of a Combined Cycle integrated Thermal Energy Storage “CiTES” system, calculated the key performance parameters like power efficiency and costs, and proved its commercial value with full-year simulations for several US electricity markets with high degree of variable renewable generation and volatile hourly electricity prices. The core element of this project is the Electro Thermal Energy Storage (ETES) technology from Siemens Gamesa Renewable Energy GmbH, using thermally stable and inexpensive volcanic rocks as storage material and air as heat transfer medium. This technology is backed by more than 10 years of experience and a 440MMBTU (130MWh-th) pilot plant in Hamburg, Germany, which is in operation since 2019. The integration of this thermal storage in an existing combined cycle power plant (CCPP) is typical power plant technology without any major technology risks. It allows the storage of inexpensive renewable energy during times of surplus renewable generation and the discharge of this energy in times of high energy demand when the fossil plant is in operation. This supplements the fossil power generation with CO2-emission-free energy. The secondary effect of the CiTES system is that a small part of the stored thermal energy is used to keep the heat recovery steam generator (HRSG) and steam turbine (ST) of the combined cycle power plant in hot and ready-to-start condition. This enables the plant to start rapidly when fossil generation is required to satisfy demand as soon variable generation drops off in the evenings or during cloud cover and calm wind periods. Without pre-warming of the HRSG and ST, the CCPP would need several hours for a cold or warm start, burn a lot of gas and release high NOx emissions during start and wouldn’t be able to use the short times of high energy prices in an efficient or economical manner. The economic parameters of CiTES were determined by a full year “8760” simulation using a data set calculation for each of the hours of the year, and historical electricity and gas prices. For consistency, the simulations were focused on the pre-COVID year 2019. The financially most attractive markets were in the Energy Reliability Council of Texas (ERCOT) region, which allowed substantial value generation with arbitrage (charge with cheap energy during renewable surplus times and discharge when energy is needed and expensive). The improvement of flexibility with the CiTES system by pre-heating and warm-keeping of the CCPP allowed for additional power generation during short time periods when demand is high but renewable generation is down; when the hourly energy prices are highest in these markets. The simulations are based on 2019 data, when ERCOT had 27GW of installed photovoltaic (PV) and wind generation. They showed that the created revenue with the prototypically sized CiTES system of 1,000MMBTU (300MWh-th) falls a little bit short of what is expected from a commercially viable investment. The system has optimization opportunities for cost reduction and increased effectiveness which will be realized during a potential Phase II Pre-FEED study following this project. Furthermore, it is safe to assume that a lot of renewable generation capacity will be added all over the US in the coming years. As an example, ERCOT is predicting to more than double its renewable generation from 27GW in 2019 to a forecasted 63GW in 2023. This will increase the amount of renewable overproduction exponentially. This rapid increase of local overproduction and the need to curtail renewable generation is well documented by the California ISO (www.CAISO.com / managing oversupply). However, the simulations also revealed a weakness in the structure of the electricity markets in the US. More specifically, when electricity prices are very low and approaching negative levels, the owners of Variable Renewable Energy (VRE) will curtail a part of their facility to stabilize the price by reducing supply. This results in a situation in which storage facilities, which are integrated in existing fossil assets and don’t have the behind-the-meter benefit of a VRE, won’t be able to purchase low cost – otherwise curtailed – renewable energy off the grid. A special tariff, which motivates VRE owners to sell otherwise curtailed renewable energy to storage facilities (Hydrogen, thermal, pumped hydro, etc.) can solve this issue. The implementation of such a regulating tariff by Independent System Operators, thus avoiding renewable curtailment, is a pre condition for successful commercialization for renewable energy storage technologies. With this advancement of design and technology and improvements in the market environment, it can be expected that the Combined Cycle integrated Thermal Energy Storage proves itself as an important innovation to keep highly efficient, natural gas-based power generation economically successful and relevant for the power industry in the United States of America.

Wolf, Thorsten↗
DOE OSTI2020

Progress in modelling fast-ion D-alpha spectra and neutral particle analyzer fluxes using FIDASIM

FIDASIM is a code that models signals produced by charge-exchange reactions between neutrals and ions (both fast and thermal) in magnetically confined plasmas. With the ion distribution function as input, the code predicts the efflux to a neutral particle analyzer diagnostic and the photon radiance of Balmer-alpha light to a fast-ion D α diagnostic, in addition to many other related quantities. A new, parallelized version of the Monte Carlo code FIDASIM has been developed in Fortran90 that is substantially faster than the original interactive data language version. Modified algorithms include more accurate treatments of the time dependent collisional-radiative equations that describe neutral energy levels, of the cloud of ‘halo’ neutrals that surround the injected neutral beam, and of finite Larmor radius effects. Enhanced physics capabilities include modelling ‘passive’ signals from cold edge neutrals, the ability to treat general three-dimensional magnetic confinement configurations, and calculations of diagnostic-specific weight functions that enable tomographic reconstructions of the fast-ion distribution function. Neutral beam attenuation, beam emission, and fast-ion birth profiles are also modelled. Finally, the new algorithms have been successfully validated against experimental data and new features have been tested through benchmarks between two independently developed versions of the code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Thermal analysis of RHIC arc dipole magnet cold mass with EIC beam screen

The existing RHIC storage rings – including their superconducting magnet arcs – will be used for the hadron storage ring of the Electron-Ion Collider (EIC). The vacuum chamber of these magnets was not designed for the EIC hadron beams, with shorter bunches and of higher average current than the RHIC beams. With the current stainless steel beam pipe, the resistive-wall (RW) heating will exceed the dynamic heat load budget. Limiting the RW heating is important to prevent the superconducting magnets from quenching and to maintain a low screen temperature necessary to impede the rise of RW heating (higher resistance at higher temperature) as well as to achieve desired ultra-high vacuum. In addition, simulations predict the formation of electron cloud which would further contribute to the dynamic heat load and could compromise the quality and stability of the beam. To reduce the resistive-wall heating and suppress electron cloud, a beam screen will be installed in the vacuum chamber of the RHIC SC magnets. The screen will have a high RRR copper layer at its inner face – useful to reduce the resistive-wall impedance thanks to its high conductivity especially at cryogenic temperatures – and will be coated with a thin layer of amorphous carbon, a material with low secondary electron yield to suppress the formation of electron clouds. The baseline solution envisages a screen that will be cooled by thermal contact to the 4.55 K beam pipe. Detailed thermal analysis have been conducted in ANSYS 2020 for an arc dipole cold mass equipped with a beam screen in order to study the feasibility of a passively-cooled screen and guide its design. Temperature-dependent thermal conductivity properties of all materials in the operating (cryogenic) temperature range are considered. Suitable assumptions and simplifications are made to model the magnet coil and calculate its homogenized thermal conductivity. Sensitivity studies with respect to layer thicknesses and area of contact are carried out and results are presented.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Exploring the impact of surface topography on Rayleigh-Bénard dry convection in the Pi cloud chamber using OpenFOAM: In cylindrical and rectangular geometries

The Pi convection-cloud chamber can generate steady-state turbulence in both rectangular and cylindrical shapes via Rayleigh-Bénard convection (RBC) by maintaining warm bottom and cold top surfaces. Although most experiments in the Pi chamber were conducted in cylindrical shapes, all previous Pi chamber simulations were conducted in a rectangular shape due to the limitations of those models to discretize a cylindrical domain when using the finite difference method therein. Here, we use OpenFOAM, an open-source finite-volume-based Computational Fluid Dynamics (CFD) software package, to conduct Large-Eddy Simulation (LES) of dry RBC in the Pi chamber at high Rayleigh numbers (10 8 to 10 9 ). Results show that large-scale circulation (LSC) direction varies in the chamber with a constant side wall temperature. Imposing a slight temperature imbalance at the side wall ranging from 0.1 to 0.7 degrees can lock the LSC, aligning better with Pi chamber observations, particularly at higher Rayleigh numbers. In addition, we examine the impact of surface topography on LSC and heat transfer in RBC systems within cylindrical and rectangular shapes under varying conditions. Results show that roughing top/bottom surfaces by adding bars of a few tens millimeters height can strengthen thermal plumes and enhance temperature fluctuations in the chamber. Furthermore, we observe that different bar height configurations lead to notable changes in LSC orientation and thermal stratification, highlighting the complex interactions between surface features and convection patterns. This finding highlights how surface topography and chamber geometry affect Rayleigh-Bénard convection, improving understanding of turbulent heat transfer and atmospheric boundary-layer processes. Direct Numerical Simulations (DNS) are also conducted to validate LES results. In conclusion, while LES effectively captures qualitative behaviors seen in DNS, it tends to underestimate velocity variances near walls, illustrating a trade-off between computational efficiency and accuracy.

54 ENVIRONMENTAL SCIENCES↗