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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.

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DOE OSTI2022

Dimensionless parameters for cloudy Rayleigh-Bénard convection: Supersaturation, Damköhler, and Nusselt numbers

In steady-state Rayleigh-Bénard convection, heat is transported by turbulent thermal convection from the bottom, hot surface to the top, cold surface, leading to a height-independent sensible heat flux. When water vapor is present and cloud formation occurs, there is also an additional latent heat flux. Heat transport in cloudy Rayleigh-Bénard convection depends on turbulent flow as well as the microphysical state of the clouds: specifically, whether substantial supersaturations exist and whether cloud liquid water is removed through sedimentation/precipitation. In this article we bridge between the Rayleigh-Bénard convection literature and the atmospheric literature. We express the governing equations for cloudy convection in dimensionless form, thereby explicitly identifying the governing parameters relevant to the cloudy case, including Schmidt, Damköhler, supersaturation, and sedimentation numbers. We further connect to the atmospheric literature by obtaining a Nusselt number (dimensionless heat flux) for a cloud-convection system, directly from the conservation equations for temperature and water vapor. This flux has the same form as that identified by Zhang et al. [L. Zhang, K. L. Chong, and K.-Q. Xia, J. Fluid Mech. 874, 1041 (2019)] for convection with water vapor, but is extended to the cloudy case. For equal thermal and water vapor diffusivities, the flux corresponds to the widely used atmospheric quantities equivalent temperature and moist static energy. Using large eddy simulation (LES) of an idealized cloudy Rayleigh-Bénard convection system with fixed boundary conditions, we find that the equivalent heat flux (Nusselt number) is only weakly dependent on the microphysical details of the system, such as liquid water mixing ratio and cloud droplet number concentration. Finally, from the results, we show the vertical profiles of sensible and latent heat fluxes depend on the liquid water content, whereas the equivalent heat flux remains a constant throughout the height of the chamber.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

User Access to Scientific Facilities via 5G: A Cyber Security Thought Experiment

5G is more than an over-the-air radio technology upgrade. It is a strategy to extend Mobile Network Operator service offerings beyond traditional voice, instant messaging and Internet access. 5G Mobile Network Operators will offer new telecommunication services that include enhanced guarantees of confidentiality, integrity and availability. How could such services change the way Science collaborations connect scientists to supercomputers and other scientific facilities? Current scientific collaborations implicitly trust cloud service providers to securely store and process data. The perceived risks of outsourcing Science data security are counterbalanced by assurances that cloud providers operate at a scale that allows them to implement security measures impractical for Science collaborations (e.g. continuous system administrator behavioral monitoring and strict individual separation of duties). If that is true for a cloud service provider like Amazon Web Services (2018 revenue: $25.7 billion), could it also be true for Mobile Network Operators like Verizon Wireless (2018 revenue: $91.7 billion) or AT&T Mobility (2018 revenue: $71.3 billion)? DOE Leadership Class supercomputer facility users currently access them from the public Internet via Secure Shell. The sponsors and operators of the supercomputer facilities have determined that the public Internet path between the Scientist’s Device and the Login Node does not natively provide enough confidentiality or integrity to protect those communications. Therefore, the facilities achieve additional confidentiality and integrity by requiring Secure Shell encryption across those untrusted network paths. Using 5G Network Slice technology, a Mobile Network Operator may offer communication services between supercomputer users and facilities that natively provide confidentiality and integrity guarantees. Sponsors and operators of supercomputer facilities may determine that these guarantees provide enough confidentiality and integrity to protect those communications. If so, a 5G Network Slice could replace an SSH session running over the public Internet. Finally, this use case could be extended to other Office of Science user facility access requirements. Consider microscopy instruments at (e.g.) the Center for Nanoscale Materials or the Environmental Molecular Sciences Laboratory. The embedded systems controlling such instruments may not always support encrypted network access technologies like SSH. 5G Network Slices may offer an alternative to current VPN or SSH tunneling techniques, with additional benefits like guaranteed minimum bandwidth.

5G↗

DOE OSTI2022

Laboratory Measurements of Cloud Scavenging of Interstitial Aerosol in a Turbulent Environment (Final Technical Report)

The link between aerosol particles and clouds is well established. Every cloud droplet forms on a preexisting particle; clouds are the primary removal mechanism for aerosol particles with diameters in the range of 0.1 to 1 micrometer. Traditionally, those connections have been considered in the absence of the chaotic air motions (turbulence) that are ubiquitous in Earth’s atmosphere. Recent work at Michigan Tech indicates that turbulent fluctuations in temperature and water vapor, which couple aerosols and cloud droplets, play an important role in whether particles grow to the size of cloud droplets and scavenging by diffusion. In this project, we measured, in a turbulent environment, the rate at which aerosol particles are incorporated into cloud droplets through both these processes, which Michigan Tech's turbulent cloud chamber enables because we can sustain a mixing cloud almost indefinitely.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

A Search for Correlations between Turbulence and Star Formation in LITTLE THINGS Dwarf Irregular Galaxies

Turbulence has the potential for creating gas density enhancements that initiate cloud and star formation (SF), and it can be generated locally by SF. To study the connection between turbulence and SF, we looked for relationships between SF traced by FUV images, and gas turbulence traced by kinetic energy density (KED) and velocity dispersion (v {sub disp}) in the LITTLE THINGS sample of nearby dIrr galaxies. We performed 2D cross-correlations between FUV and KED images, measured cross-correlations in annuli to produce correlation coefficients as a function of radius, and determined the cumulative distribution function of the cross-correlation value. We also plotted on a pixel-by-pixel basis the locally excess KED, v {sub disp}, and H i mass surface density, Σ{sub HI}, as determined from the respective values with the radial profiles subtracted, versus the excess SF rate density Σ{sub SFR}, for all regions with positive excess Σ{sub SFR}. We found that Σ{sub SFR} and KED are poorly correlated. The excess KED associated with SF implies a ∼0.5% efficiency for supernova energy to pump local H i turbulence on the scale of the resolution here, which is a factor of ∼2 too small for all of the turbulence on a galactic scale. The excess v {sub disp} in SF regions is also small, only ∼0.37 km s{sup −1}. The local excess in Σ{sub HI} corresponding to an excess in Σ{sub SFR} is consistent with a H i consumption time of ∼1.6 Gyr in the inner parts of the galaxies. The similarity between this timescale and the consumption time for CO implies that CO-dark molecular gas has comparable mass to H i in the inner disks.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2023

A 5G Enabled Adaptive Computing Workflow for Greener Power Grid

5G wireless technology can deliver higher data speeds, ultra low latency, more reliability, massive network capacity, increased availability, and a more uniform user experience to users. It brings additional power to help address the challenges brought by renewable integration and decarbonization. In this paper, a 5G enabled adaptive computing workflow tool has been presented that consists of various computing resources, such as 5G equipment, edge computing, cluster, Graphics processing unit (GPU) and cloud computing, with two examples showing technical feasibility for edge-grid-cloud interaction for real-time monitoring, security assessment, and forecasting. Benefiting from the high data transmission speed and massive connection capability of 5G, the workflow shows its potential to seamlessly integrate various applications at distributed and/or centralized locations to build more complex and powerful functions, with better flexibility.

5G technology, computational workflow, edge comput↗

DOE OSTI2023

CCSI Toolset 3.17 Release

CCSI Toolset 3.17 Release Highlights A workaround was developed to allow complex Aspen Custom Modeler (ACM) models to be used in FOQUS. This workaround uses Visual Basic for Applications to connect the ACM models to FOQUS. The ability for User plugins to be uploaded to FOQUS Cloud was added. The documentation was updated to include Optional Software Install and Tutorial Notes to clarify the usage of Turbine and SimSinter in installation instructions and adds a link to the relevant tutorial page. The Sequential Design of Experiments documentation was updated with current screenshots. The copyright was updated to include 2023.

AS↗

DOE OSTI2023

Cloud Services Enable Efficient AI-Guided Simulation Workflows across Heterogeneous Resources

Applications which fuse machine learning and simulation are rarely best served by a single computing resource. Highly parallel simulation codes are best deployed on super- computers, while AI tasks used to decide which simulations to perform may be best suited to specialized accelerators. Here we present a Function-as-a-Service (FaaS) system for executing complex, distributed computational campaigns that achieves performance parity with conventional workflow systems without the complexities of secure network connections between compute providers. One innovation enabling high performance is a subsystem that directly moves task data between sites, separate from the cloud-hosted FaaS system used to distribute task instructions. We also introduce a flexible scheduling system that allows us access factor of 2 trade offs between the amount of resources required to solve a problem at each compute site. We anticipate that this system will upgrade multi-site applications from demonstration projects to routine practice in computational science.

Ward, Logan↗

DOE OSTI2024

Science Use Case Design Patterns for Autonomous Experiments

Connecting scientific instruments and robot-controlled laboratories with computing and data resources at the edge, the Cloud or the high-performance computing (HPC) center enables autonomous experiments, self-driving laboratories, smart manufacturing, and artificial intelligence (AI)-driven design, discovery and evaluation. The Self-driven Experiments for Science / Interconnected Science Ecosystem (INTERSECT) Open Architecture enables science breakthroughs using intelligent networked systems, instruments and facilities with a federated hardware/software architecture for the laboratory of the future. It relies on a novel approach, consisting of (1) science use case design patterns, (2) a system of systems architecture, and (3) a microservice architecture. This paper introduces the science use case design patterns of the INTERSECT Architecture. It describes the overall background, the involved terminology and concepts, and the pattern format and classification. It further offers an overview of the 12 defined patterns and 4 examples of patterns of 2 different pattern classes. It also provides insight into building solutions from these patterns. The target audience are computer, computational, instrument and domain science experts working in the field of autonomous experiments.

Engelmann, Christian↗

DOE OSTI2022

A Fast VANET-Assisted Scheme for Event Data Recorders

An event data recorder (EDR) is a device installed in a vehicle to record information. Similar to a black box in an airplane, an EDR is used in the study of automobile accidents. Many schemes have been proposed that use vehicle network technology to help record EDR data, including schemes involving storing data on roadside units or nearby vehicles and schemes leveraging blockchain technology. However, these schemes do not take into account the vehicle company’s server; with the increased use of autonomous vehicles, the data related to these vehicles are always uploaded to the vehicle company’s server. In this scenario, we classify the situation into different cases, according to whether or not it is an emergency and whether the vehicle and the server are connected. For these cases, we propose a scheme whereby a vehicle uploads the EDR data to a cloud server and sends the evidence of storage to the nearby vehicle through a vehicular ad hoc network. Our scheme offers a fast response due to the use of symmetric cryptography algorithms while also considering security requirements.

Liu, Wei↗

DOE OSTI2023

INTERSECT Architecture Specification: Use Case Design Patterns (V.0.9)

Connecting scientific instruments and robot-controlled laboratories with computing and data resources at the edge, the Cloud or the high-performance computing (HPC) center enables autonomous experiments, self-driving laboratories, smart manufacturing, and artificial intelligence (AI)-driven design, discovery and evaluation. The Self-driven Experiments for Science / Interconnected Science Ecosystem (INTERSECT) Open Architecture enables science breakthroughs using intelligent networked systems, instruments and facilities with a federated hardware/software architecture for the laboratory of the future. It relies on a novel approach, consisting of (1) science use case design patterns, (2) a system of systems architecture, and (3) a microservice architecture. This document introduces the science use case design patterns of the INTERSECT Architecture. It describes the overall background, the involved terminology and concepts, and the pattern format and classification. It further details the 12 defined patterns and provides insight into building solutions from these patterns. The document also describes the application of these patterns in the context of several INTERSECT autonomous laboratories. The target audience are computer, computational, instrument and domain science experts working in the field of autonomous experiments.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

A Review of Edge Computing Technology and Its Applications in Power Systems

Recent advancements in network-connected devices have led to a rapid increase in the deployment of smart devices and enhanced grid connectivity, resulting in a surge in data generation and expanded deployment to the edge of systems. Classic cloud computing infrastructures are increasingly challenged by the demands for large bandwidth, low latency, fast response speed, and strong security. Therefore, edge computing has emerged as a critical technology to address these challenges, gaining widespread adoption across various sectors. This paper introduces the advent and capabilities of edge computing, reviews its state-of-the-art architectural advancements, and explores its communication techniques. A comprehensive analysis of edge computing technologies is also presented. Furthermore, this paper highlights the transformative role of edge computing in various areas, particularly emphasizing its role in power systems. It summarizes edge computing applications in power systems that are oriented from the architectures, such as power system monitoring, smart meter management, data collection and analysis, resource management, etc. Additionally, the paper discusses the future opportunities of edge computing in enhancing power system applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Application of remote sensing precipitation data and the $\mathrm{CONNECT}$ algorithm to investigate spatiotemporal variations of heavy precipitation: Case study of major floods across Iran (Spring 2019)

In recent years, the number of floods following unprecedented rainfall events have increased in Iran during early spring (March 21st to April 20th, referred to in Iran as the month of “Farvadin”). While numerous studies have addressed changes in climate extremes and precipitation trends at different temporal scales from daily to annual across the country, analyses of short-duration and heavy precipitation, especially during recent years, are rarely considered. Furthermore, most studies investigate the variations in extremes and total precipitation using a limited number of synoptic weather stations across Iran. Here this study assesses the variations in heavy precipitation (precipitation with intensities greater than or equal to 3 mm/3 h) at 0.04° spatial and 3-hourly temporal resolution during the month of Farvardin. In addition, the effect of atmospheric river conditions over Iran and their possible link to intensifying heavy precipitation is explored. For this purpose, the CONNected-objECT (CONNECT) algorithm is applied on a precipitation dataset, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS), and an Integrated Water Vapor Transport (IVT) dataset from the NASA Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2). The results suggest that the increase in the number of floods in recent years is related to the increase in the intensity and volume of heavy precipitation events, although the frequency and duration of heavy precipitation events have not changed significantly. Furthermore, the results show that atmospheric river conditions over the country are present during the same window as each year’s most extreme events. It is found that 8 out of 13 of the largest ARs over Iran come from moisture plumes with pathways over the African and Red Sea.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Use of Remote Sensing and In-Situ Observations to Develop and Evaluate Improved Representations of Convection and Clouds for the ACME Model

The overachieving goal of the whole CMDV-MCS project is to improve understanding of warm season continental convection and to develop treatments of convection and microphysics capable of representing mesoscale convective systems (MCSs) features in large-scale models. Our tasks for this project contributing to the overachieving goal include: (1) Improve the ice nucleation formulation for MG2 and P3 cloud microphysics schemes; (2) Improve the treatment of subgrid dynamics and thermodynamics driving the ice nucleation in E3SM; and (3) Test the performance of improved ice microphysics in E3SM with observation data. In this project, we have (1) Improved the ice nucleation parameterization for MG2 and P3 in E3SM by implementing two advanced empirical parameterizations with connection to aerosols. The two deterministic heterogeneous ice nucleation parameterizations (i.e., DeMott et al., 2015; Niemand et al., 2012) were merged with the MG2 and P3 cloud microphysics schemes in E3SM. Long-term simulations were conducted to examine the impacts of these new parameterizations on simulated cloud properties; (2) Improved the treatment of subgrid dynamics and thermodynamics driving the ice nucleation in E3SM. We evaluated the double Gaussian PDF of vertical velocity simulated by the Cloud Layers Unified By Binormals (CLUBB) and the sub-column vertical velocity sampled from the Subgrid Importance Latin Hypercube Sampler (SILHS) in E3SM. We introduced the vertical velocity variance induced by topographic gravity waves for ice nucleation and droplet activation; and (3) Tested the performance of improved ice microphysics in E3SM with observation data. We tested the new treatments of ice nucleation in the single column model (SCM) mode for the stratiform mixed-phase clouds observed during 9-10 October 2004 in the DOE ARM Mixed-Phase Arctic Cloud Experiment (M-PACE) and for the convective clouds observed on 20 May 2011 in the Midlatitude Continental Convective Clouds Experiment (MC3E). Modeled ice nucleating particles (INPs) concentrations were compared against observations collected around the globe.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

The Lack of a QBO-MJO Connection in Climate Models With a Nudged Stratosphere

The observed stratospheric quasi-biennial oscillation (QBO) and the tropospheric Madden-Julian oscillation (MJO) are strongly connected in boreal winter, with stronger MJO activity when lower-stratospheric winds are easterly. However, the current generation of climate models with internally generated representations of the QBO and MJO do not simulate the observed QBO-MJO connection, for reasons that remain unclear. Furthermore, this study builds on prior work exploring the QBO-MJO link in climate models whose stratospheric winds are relaxed toward reanalysis, reducing stratospheric biases in the model and imposing a realistic QBO. A series of ensemble experiments are performed using four state-of-the-art climate models capable of representing the MJO over the period 1980–2015, each with similar nudging in the stratosphere. In these four models, nudging leads to a good representation of QBO wind and temperature signals, however no model simulates the observed QBO-MJO relationship. Biases in MJO vertical structure and cloud-radiative feedbacks are investigated, but no conclusive model bias or mechanism is identified that explains the lack of a QBO-MJO connection.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Emulation and detection of physical faults and cyber-attacks on building energy systems through real-time hardware-in-the-loop experiments

The increasing use of remote or mobile access, integrated wearable technologies, data exchange, and cloud-based data analytics in modern smart buildings is steering the building industry towards open communication technologies. The increased connectivity and accessibility could lead to more cyber-attacks in smart buildings. On the other hand, physical faults (e.g., HVAC -heating, ventilation, and air-conditioning faults) may have similar adverse impacts as those from the cyber-attacks on building energy systems, such as occupant discomfort, energy wastage, and equipment downtime. However, current physical behavior-based anomaly detection methods fail to differentiate between cyber-attacks and physical faults in building energy systems. Moreover, the challenge in collecting real-world threat data with ground truth has led researchers to rely on numerical models with user-defined assumptions, which may not accurately reflect real-world conditions due to the lack of in-situ experimental datasets. To address these challenges and gaps, this paper presents a flexible hardware-in-the-loop (HIL) testbed for generating cyber-attack and physical fault datasets and demonstrating threat detection algorithms in a real building automation system (BAS) environment. This testbed combines hardware (i.e., real BAS with local HVAC controllers and a physical network) with software (i.e., high-fidelity models to represent behaviors of building envelope and HVAC energy systems), enabling emulations of realistic threats. Five HIL experiments, including one baseline without any threats, two with physical faults, and two with cyber-attacks, were conducted to generate datasets containing detailed network traffic and system states. A joint classification framework, incorporating a network analyzer and a physical HVAC fault detector, was proposed to automatically detect cyber-physical abnormalities on BAS at both the network and the physical HVAC levels. The network analyzer comprises a conditional random fields (CRF) based command validator and a statistics-based detection strategy. The fault detector employs a weather and schedule-based pattern matching and feature-based principal component analysis (WPM-FPCA) method. Evaluation of the classification using four metrics from the multi-class confusion matrix revealed an average accuracy of 90.2%, recall of 89.7%, precision of 88.5% and F1-score of 89.2%. Finally, these results demonstrate that the proposed joint classification framework can effectively differentiate between specific types of cyber-attacks (e.g., device reinitialization attack, network Denial-of-Service attack) and physical faults (e.g., air handling unit operational fault, cooling coil valve stuck) in real time for improved building energy management.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Colossal Optical Anisotropy from Atomic-Scale Modulations

Materials with large birefringence (Δn, where n is the refractive index) are sought after for polarization control (e.g., in wave plates, polarizing beam splitters, etc.), nonlinear optics, micromanipulation, and as a platform for unconventional light–matter coupling, such as hyperbolic phonon polaritons. Layered 2D materials can feature some of the largest optical anisotropy; however, their use in most optical systems is limited because their optical axis is out of the plane of the layers and the layers are weakly attached. This work demonstrates that a bulk crystal with subtle periodic modulations in its structure—Sr 9/8 TiS 3 —is transparent and positive-uniaxial, with extraordinary index n e = 4.5 and ordinary index n o = 2.4 in the mid- to far-infrared. The excess Sr, compared to stoichiometric SrTiS 3 , results in the formation of TiS 6 trigonal-prismatic units that break the chains of face-sharing TiS 6 octahedra in SrTiS 3 into periodic blocks of five TiS 6 octahedral units. The additional electrons introduced by the excess Sr form highly oriented electron clouds, which selectively boost the extraordinary index n e and result in record birefringence (Δn > 2.1 with low loss). The connection between subtle structural modulations and large changes in refractive index suggests new categories of anisotropic materials and also tunable optical materials with large refractive-index modulation.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Multifaceted aerosol effects on precipitation

Aerosols have been proposed to influence precipitation rates and spatial patterns from scales of individual clouds to the globe. However, large uncertainty remains regarding the underlying mechanisms and importance of multiple effects across spatial and temporal scales. Here, in this study, we review the evidence and scientific consensus behind these effects, categorized into radiative effects via modification of radiative fluxes and the energy balance, and microphysical effects via modification of cloud droplets and ice crystals. Broad consensus and strong theoretical evidence exist that aerosol radiative effects (aerosol–radiation interactions and aerosol–cloud interactions) act as drivers of precipitation changes because global mean precipitation is constrained by energetics and surface evaporation. Likewise, aerosol radiative effects cause well-documented shifts of large-scale precipitation patterns, such as the intertropical convergence zone. The extent of aerosol effects on precipitation at smaller scales is less clear. Although there is broad consensus and strong evidence that aerosol perturbations microphysically increase cloud droplet numbers and decrease droplet sizes, thereby slowing precipitation droplet formation, the overall aerosol effect on precipitation across scales remains highly uncertain. Global cloud-resolving models provide opportunities to investigate mechanisms that are currently not well represented in global climate models and to robustly connect local effects with larger scales. This will increase our confidence in predicted impacts of climate change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

The TELPERION survey for distant [O iii ] clouds around luminous and hibernating AGN

ABSTRACT We present a narrow-band [O iii] imaging survey of 111 active galactic nucleus (AGN) hosts and 17 merging-galaxy systems, in search of distant extended emission-line regions (EELRs) around AGNs (either extant or faded). Our data reach deeper than detection from the broad-band SDSS data and cover a wider field than some early emission-line surveys used to study extended structure around AGNs. Spectroscopic follow-up confirms two new distant AGN-ionized clouds, in the merging systems NGC 235 and NGC 5514, projected at 26 and 75 kpc from the nuclei (respectively). We also recover the previously known region in NGC 7252. These results strengthen the connection between EELRs and tidal features; kinematically quiescent distant EELRs are virtually always photoionized tidal debris. We see them in ≈10 per cent of the galaxies in our sample with tidal tails. Energy budgets suggest that the AGN in NGC 5514 has faded by >3 times during the extra light traveltime ≈250 000 yr from the nucleus to the cloud and then to the observer; strong shock emission in outflows masks the optical signature of the AGN. For NGC 235 our data are consistent with but do not unequivocally require variation over ≈85 000 yr. In addition to these very distant ionized clouds, we find luminous and extensive line emission within four galaxies – IC 1481, ESO 362-G08, NGC 5514, and NGC 7679. Among these, IC 1481 shows apparent ionization cones, a rare combination with its LINER AGN spectrum. In NGC 5514, we measure a 7-kpc shell expanding at ≈370 km s−1 west of the nucleus.

79 ASTRONOMY AND ASTROPHYSICS↗