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At least 397 records · Page 22

A Co-Simulation Framework for Steady-State Analyses of Multiple Droop-based MTdc Grids in Continental-Scale Systems

The growing scale and complexity of planning continental hybrid ac and multi-terminal dc (MTdc) systems require scalable steady-state modeling and analysis approaches not currently available in commercial tools. This paper presents a comprehensive multi-fidelity model-conversion framework that enables the efficient transition of MTdc grid models from production cost modeling (PCM) and approximated ac power flow to detailed ac–MTdc power flow for large-scale planning studies. The core of this framework is a scalable co-simulation approach that, for the first time, enables power flow analysis in continental-scale ac–MTdc systems. It seamlessly couples commercial ac solvers with a detailed MTdc grid model that incorporates droop-based control and current-limiting strategies of multiple meshed MTdc grids. Leveraging this capability, an evaluation framework to systematically assess and compare different MTdc power redispatch strategies under ac and dc contingencies is introduced. The proposed framework and algorithm are evaluated using a combined Western and Eastern Interconnection system with 11 MTdc grids of various sizes, showing a coherent transition from PCM to detailed ac–MTdc power flow and improved system performance in voltage regulation and line overload mitigation following typical contingencies.

Nguyen, Quan H.↗

Isolation and characterization of 24 phages infecting the plant growth-promoting rhizobacterium Klebsiella sp. M5al

Bacteriophages largely impact bacterial communities via lysis, gene transfer, and metabolic reprogramming and thus are increasingly thought to alter nutrient and energy cycling across many of Earth’s ecosystems. However, there are few model systems to mechanistically and quantitatively study phage-bacteria interactions, especially in soil systems. Here, we isolated, sequenced, and genomically characterized 24 novel phages infectingKlebsiellasp. M5al, a plant growth-promoting, nonencapsulated rhizosphere-associated bacterium, and compared many of their features against all 565 sequenced, dsDNAKlebsiellaphage genomes. Taxonomic analyses revealed that theseKlebsiellaphages belong to three known phage families (Autographiviridae,Drexlerviridae, andStraboviridae) and two newly proposed phage families (CandidatusMavericviridaeand Ca.Rivulusviridae). At the phage family level, we found that core genes were often phage-centric proteins, such as structural proteins for the phage head and tail and DNA packaging proteins. In contrast, genes involved in transcription, translation, or hypothetical proteins were commonly not shared or flexible genes. Ecologically, we assessed the phages’ ubiquity in recent large-scale metagenomic datasets, which revealed they were not widespread, as well as a possible direct role in reprogramming specific metabolisms during infection by screening their genomes for phage-encoded auxiliary metabolic genes (AMGs). Even though AMGs are common in the environmental literature, only one of our phage families,Straboviridae, contained AMGs, and the types of AMGs were correlated at the genus level. Host range phenotyping revealed the phages had a wide range of infectivity, infecting between 1–14 of our 22 bacterial strain panel that included pathogenicKlebsiellaandRaoultellastrains. This indicates that not all capsule-independent Klebsiella phages have broad host ranges. Together, these isolates, with corresponding genome, AMG, and host range analyses, help build theKlebsiellamodel system for studying phage-host interactions of rhizosphere-associated bacteria.

Science & Technology - Other Topics↗

Overview of TAE technologies’ HHFW project on LAPD

Simulation survey performed at TAE Technologies, has demonstrated that high harmonic fast wave (HHFW) heating is a promising scenario to heat core electrons of FRC plasma. To prepare the proposed experimental study of HHFW antenna-plasma coupling and wave propagation on LAPD machine at UCLA, a high-power-capable 4-strap antenna has been calculated and designed through collaboration among TAE, ORNL, ASIPP, and UCLA. This antenna was mechanically designed and fabricated by ASIPP and it has been installed recently on LAPD. Meanwhile, by using the Petra-M code, a newly developed generic electromagnetic simulation tool for modeling RF wave propagation, the RF-SciDAC team starts 3D full wave simulations. Detailed information on antenna electromagnetic simulations and mechanical design, as well as preliminary experimental results of wave propagation study with the newly installed phased- array antenna, will be presented in this paper.REFE

Yang, Xiaokang↗

Standard Candles for Supernova Neutrino Detection at DUNE

The Deep Underground Neutrino Experiment (DUNE) far detector is sensitive to $\mathcal{O}(10)$ MeV electron neutrinos through $ν_e$ charged-current reaction with argon. This capability is a unique window into the $ν_e$ component of a Galactic core-collapse supernova flux. Extracting the properties of the supernova spectrum is, however, limited by the poorly-known $ν_e$-Ar cross section. We propose a data-driven strategy that leverages $^8$B solar neutrinos and muon-decay-at-rest neutrinos as standard candles for this process. These calibration samples constrain both the low-energy and high-energy components of the cross section relevant for supernova detection. Our method reduces the reliance on nuclear models, which can bias the extraction of the spectral parameters by as much as 300$\%$.

Cheng, Ting [Fermilab]↗

AI-Enabled Discovery and Physics-Based Optimization of Energy Efficient Processing Strategies for Advanced Turbine Alloys (Final Technical Report)

In this project, the multi-organizational team of academic and industrial researchers from the University of Kentucky an aerospace and energy generation OEM partner has leveraged novel Digital Process Twin (DPT) models of process/structure interactions (i.e., process-induced surface integrity) to advance a paradigm of fully integrated computational materials engineering (ICME). Using efficient process models as the core of a digital process simulator for a reinforcement learning algorithm, the team has integrated industrial data and metrics of structure/performance/energy relationships and manufacturing-related energy metrics to optimize dynamic processing parameters for significantly improved life-cycle energy efficiency of advanced γ-TiAl low-pressure turbine (LPT) alloys, as indicated by a set of design relevant parameters (e.g., residual stresses and scrap rate). The key objective and anticipated outcome of the project was at least a 10% reduction in life-cycle embodied energy for a recently developed, γ-TiAl low-pressure turbine (LPT) alloy and nickel-based superalloy Inconel 718, through the adoption of the proposed AI-enabled process optimization approach. The final project outcomes significantly exceeded this original target, realizing manufacturing-related energy efficiency improvements of more than 130% for TiAl and up to 80% for Inconel 718. Rather than following the prevailing and highly inefficient empirical paradigm, the proposed study demonstrated the feasibility of adopting a digital, physics-based process design and optimization paradigm. The recurring need for manual intervention, rework, reinspection causes significant production bottlenecks and unnecessary expense associated with delivering the requisite component quality. The OEM partner, and turbine industry in general, expect to reap significant cost and resource savings if an AI-optimized set of parameters can be applied to specific machining operations. The technical scope of the proposed project involved the paving of a realistic path towards model-based and AI-enabled Integrated Computational Materials Engineering (ICME), and away from inefficient empirical process optimization and legacy manufacturing practices, which are no longer able to efficiently process novel high-performance turbine alloy materials. The project team will address the fundamental knowledge gap that currently exists within the ICME paradigm with respect to the process/structure/performance/energy impacts of finishing processes. While significant resources have been devoted to the ‘early stages’ of manufacturing, such as alloy design, primary and secondary processing, finishing processes have not been adequately integrated within ICME. To provide an actionable path towards model-based finishing process design (e.g., machining, burnishing, grinding, polishing), we will employ a novel AI-enabled process optimization paradigm, based on a computationally efficient, physics-based process simulator. Through limited experimental work to calibrate and validate our process simulator model via an advanced in-situ characterization technique and process optimization via reinforcement learning, the project will seek to demonstrate a viable alternative to the inefficient ‘legacy’ processing strategies, empirical testing and broad scope machining learning approaches, all of which fail to adequately consider complex process physics. The project team has identified an intermetallic γ-TiAl LPT alloy, which is currently being used as part of the OEM partner’s advanced gas turbine designs. This particular alloy poses significant manufacturing challenges during finishing operations, which limit the degree to which the current turbine design can be manufactured in an energy- and cost-efficient manner. Empirical testing and numerical modeling efforts to optimize processing parameters for γ-TiAl have not been able to resolve these manufacturing challenges, so the proposed physics-based AI-enabled optimization technology would offer a truly novel and transformative capability. The multi-organizational team of academic and industry experts from the UKY and the OEM partner will work together closely to demonstrate the analytical and experimental critical function and characteristic proof of concept of this novel approach.

20 FOSSIL-FUELED POWER PLANTS↗

Imaging of 16 distant EMSS clusters with z greater than or equal to 0.2 and L(subx,44) greater than or equal to 4: New arcs and first consequences

Medium-deep V, R, and I observations of a subsample of 16 clusters of galaxies in the Experimental Mobile Satellite System (EMSS) sample defined from the Einstein satellite data are presented. Three new cases of clusters with giant luminous arcs (length/width greater than 10, V less than 22) have been discovered together with six new arcs (4 less than l/w less than 10, V less than 22), and we propose that these arcs are new examples of gravitational lensing of background galaxies by the rich clusters. Combined with giant luminous arcs already observed in the EMSS sample, there is a total of six giant luminous arcs observed in the sample of 16 clusters. This high rate of success in finding arcs added to their axis ratio distribution is consistent with very small core radii (less than 100 kpc) for the dark matter distribution in rich clusters, and rules out models in which dark matter follows the X-ray gas.

Le Fevre, O.↗

Dual‐Scale Nanostructures via Evaporative Assembly

Abstract Dual‐scale hierarchical structures with regular microscale patterns and varying degree of nanoscale crystalline order are synthesized on physically and chemically homogeneous substrates by evaporative self‐assembly with a suspension of DNA‐functionalized nanoparticles (NPs) with a charged core shell. For a certain NP concentration range, periodic concentric rings in a stripe‐like micropattern are produced over macroscale surface areas by an NP monolayer with hexagonal lattice structure at the nanoscale. The stripe width, spacing, and nanoparticle ordering can be controlled by varying the NP concentration. The results indicate that the interplay between “stick‐slip” motion of the droplet contact line and coulombic and steric NP interactions control the formation of the observed structures. A simple analytical model is proposed to account for the experimental observations and guide the future design of different nanostructure morphologies. This work demonstrates a simple cost‐effective mask‐free method for fabricating large‐area nanostructured 2D materials and metasurfaces for applications ranging from energy conversion/storage to optoelectronics and nanophotonics.

Srivastava, Sunita↗

Development of hypersonic engine seals: Flow effects of preload and engine pressures

A new type of engine seal is being developed to meet the needs of advanced hypersonic engines. A seal braided of emerging high temperature ceramic fibers comprised of a sheath-core construction was selected for study based on its low leakage rates. Flexible, low-leakage, high temperature seals are required to seal the movable engine panels of advanced ramjet-scramjet engines either preventing potentially dangerous leakage into backside engine cavities or limiting the purge coolant flow rates through the seals. To predict the leakage through these flexible, porous seal structures as a function of preload and engine pressures, new analytical flow models are required. An empirical leakage resistance/preload model is proposed to characterize the observed decrease in leakage with increasing preload. Empirically determined compression modulus and preload factor are used to correlate experimental leakage data for a wide range of seal architectures. Good agreement between measured and predicted values are observed over a range of engine pressures and seal preloads.

Cai, Zhong↗

The Collection, Usage, and Preliminary Examination of the Apollo Sample Suite: Lessons for Artemis

Apollo Sample Collection and Usage: From 1969 to 1972 there were six Apollo missions to the surface of the Moon during which the astronauts collected 382 kg of rock and regolith (~2200 samples). The samples collected fall into these general categories: rocks (~66% by mass), rake samples (~4%), bulk regolith (~24%), and specialty regolith (deep drill cores, drive tubes, sealed bulk regolith) samples (~6%). In each category there are a variety of different subtypes available for study, e.g., among the bulk regolith samples there are also skim, trench, and (partially) shaded regolith samples each sampling unique types or depths of regolith. This variety of subsamples has enabled a multitude of different studies over the past 55 years (>3400 individual requests). We are still averaging ~50 unique requests and have allocated >500 individual Apollo samples annually for the past 10 years (2020 excepted). Looking at the 4,675 non-ANGSA (Apollo Next Generation Sample Analysis) samples allocated over the past 10 years, the proportions of allocated samples do not precisely align with the abundance (by mass) of those samples withing the collection: Rock (69.4 %); Rake (10.8 %); Bulk Regolith (15.5 %); Drive Tube (3.3 %); Core/Specialty (1.0 %). Apollo Preliminary Examination (PE): The PE process differs significantly for the various sample types enumerated above; we focus on regolith and rock samples here. During the Apollo mission era, the PE process evolved over the course of the missions; below is what was done for the Apollo 17 mission. For regolith samples, the PE process was: (1) documented bags containing regolith are opened, photographed, and described; (2) large rocks are removed and treated separately; (3) 25% to 33% of the bulk soil is scooped out, weighed, and stored in reserve; (4) the remaining sample is sieved to produce the size fractions <1, 1- 2, 2-4, and 4-10 mm, all of which are weighed. For rock samples, the process is: (1) removing rocks from the container(s) it came back from the Moon in; (2) rematching any materials that spalled off the rock to their original location; (3) numbering, weighing, and basic photographic documentation; (4) dusting with a gentle N2 gas jet; (5) Orthogonal photography; (6) detailed description of the textures and features of the rock; (7) rock modelling and measurement; (8) stereophotography; (9) determination of the orientation of the rock on the lunar surface. Drive tubes and deep drill cores were not characterized during PE beyond an initial weight and a sketch of the interior tube materials derived from 2D medical X-ray images. Catalogs: The ongoing utility of the Apollo samples is enabled by the robust cataloguing process for the samples [3-5], which allows the scientific community to accurately request samples uniquely suited to their proposed studies. A common misconception, however, is the amount of detail that goes into the initial catalog (e.g., [6]) for a collection from the preliminary examination (PE) period, versus what goes into the catalogs that come later in the life cycle of the samples from that mission (e.g., [7]). The only required data for a PE catalog is a weight, a basic photograph, and a description of the nature of the sample. Artemis PE: Over the past few years, the ongoing ANGSA project studied previously unopened Apollo 17 double drive tube samples 73001/2 [1], and a PE of the drive tubes was done. The PE took the existing core dissection process (developed during PE of Apollo cores in the 1970s, 1980s), and modernized it [7]. The main lesson from the ANGSA PE relative to future missions was that the physical work done during PE of lunar samples has not changed much over the past 5 decades. The use of “modern” technology during PE (e.g., XCT; multispectral analyses) resulted in an enhanced initial understanding of the 73001 and 73002 drive tubes, but greatly increased the time required. The lessons learned from recent astromaterial PEs (e.g., ANGSA and OREx) are important to consider when planning for Artemis, but the unique nature of the Artemis Campaign means many lessons learned from these mission will not be applicable. Given the time constraints (6 months) and likely number of samples that will be returned by Artemis (>200), the Artemis PE catalog will necessarily look much more like [4] than [6].

J Gross↗

LICS Modeling [Slides]

We propose to design a new diagnostic based on laser inverse Compton scattering (LICS) to study the dynamics of runaway electron formation during killer-pellet triggered disruptions in DIII-D, and their subsequent loss. Obtaining a better understanding of transient runaway electrons (and how to suppress them) is one of the highest priorities of the US fusion program. To enable this, we need better measurements of the runaway electron population during and after disruptions. We intend to measure point-wise time-resolved spatial profile and energy distributions of the runaway electrons while they are in the core of the tokamak plasma. While LICS measurements of relativistic e-beams have been successfully made on accelerators, they have never been done in a tokamak. We bring two innovations to this diagnostic concept which should enable 10 times better signal-to-noise ratios than previously envisioned. In particular, we will marry bright short pulse (10’s of picosecond) laser technologies with the availability of short-pulse gated x-ray imagers developed at Los Alamos for the National Ignition Facility (NIF), to reject noise generated by the tokamak and plasma environment. We will generate a Conceptual Physics Basis, a Preliminary Design, and a Final Design package, with associated DIII-D reviews, along with prototype component testing for the diagnostic over the course of the two year duration of this proposal.

42 ENGINEERING↗

Simulating Magnetized Electron Cooling for EIC with JSPEC

We present a possible electron cooling configuration for the proposed Electron Ion Collider (EIC) facility, developed using a Nelder-Mead Simplex optimization procedure built into JSPEC, an electron cooling code developed at Jefferson Lab. We show the time evolution of the emittance of the ion beam in the presence of this cooler evaluated assuming the ion distribution remains Gaussian. We also show that bi-gaussian distributions emerge in simulations of ion macro-particles. We show how intra-beam scattering can be treated with a core-tail model in simulations of ion macro-particles. The Sirepo/JSPEC* and Sirepo/Jupyter** apps will be presented, with instructions enabling the community to reproduce our simulations.

Coleman, S. J.↗

Grid Enabled Geospatial Catalogue Web Service

Geospatial Catalogue Web Service is a vital service for sharing and interoperating volumes of distributed heterogeneous geospatial resources, such as data, services, applications, and their replicas over the web. Based on the Grid technology and the Open Geospatial Consortium (0GC) s Catalogue Service - Web Information Model, this paper proposes a new information model for Geospatial Catalogue Web Service, named as GCWS which can securely provides Grid-based publishing, managing and querying geospatial data and services, and the transparent access to the replica data and related services under the Grid environment. This information model integrates the information model of the Grid Replica Location Service (RLS)/Monitoring & Discovery Service (MDS) with the information model of OGC Catalogue Service (CSW), and refers to the geospatial data metadata standards from IS0 19115, FGDC and NASA EOS Core System and service metadata standards from IS0 191 19 to extend itself for expressing geospatial resources. Using GCWS, any valid geospatial user, who belongs to an authorized Virtual Organization (VO), can securely publish and manage geospatial resources, especially query on-demand data in the virtual community and get back it through the data-related services which provide functions such as subsetting, reformatting, reprojection etc. This work facilitates the geospatial resources sharing and interoperating under the Grid environment, and implements geospatial resources Grid enabled and Grid technologies geospatial enabled. It 2!so makes researcher to focus on science, 2nd not cn issues with computing ability, data locztic~, processir,g and management. GCWS also is a key component for workflow-based virtual geospatial data producing.

Chen, Ai-Jun↗

Marine phytoplankton downregulate core photosynthesis and carbon storage genes upon rapid mixed layer shallowing

Marine phytoplankton are a diverse group of photoautotrophic organisms and key mediators in the global carbon cycle. Phytoplankton physiology and biomass accumulation are closely tied to mixed layer depth, but the intracellular metabolic pathways activated in response to changes in mixed layer depth remain less explored. Here, metatranscriptomics was used to characterize the phytoplankton community response to a mixed layer shallowing (from 233 to 5 m) over the course of two days during the late spring in the Northwest Atlantic. Most phytoplankton genera downregulated core photosynthesis, carbon storage, and carbon fixation genes as the system transitioned from a deep to a shallow mixed layer and shifted towards catabolism of stored carbon supportive of rapid cell growth. In contrast, phytoplankton genera exhibited divergent transcriptional patterns for photosystem light harvesting complex genes during this transition. Active virus infection, taken as the ratio of virus to host transcripts, increased in the Bacillariophyta (diatom) phylum and decreased in the Chlorophyta (green algae) phylum upon mixed layer shallowing. A conceptual model is proposed to provide ecophysiological context for our findings, in which integrated light limitation and lower division rates during transient deep mixing are hypothesized to disrupt resource-driven, oscillating transcript levels related to photosynthesis, carbon fixation, and carbon storage. Our findings highlight shared and unique transcriptional response strategies within phytoplankton communities acclimating to the dynamic light environment associated with transient deep mixing and shallowing events during the annual North Atlantic bloom.

59 BASIC BIOLOGICAL SCIENCES↗

Development of hypersonic engine seals - Flow effects of preload and engine pressures

A new type of engine seal is being developed to meet the needs of advanced hypersonic engines. A seal braided of emerging high temperature ceramic fibers comprised of a sheath-core construction has been selected for study based on its low leakage rates. Flexible, low-leakage, high-temperature seals are required to seal the movable engine panels of advanced ramjet-scramjet engines either preventing potentially dangerous leakage into backside engine cavities or limiting the purge coolant flow rates through the seals. To predict the leakage through these flexible, porous seal structures as a function of preload and engine pressures, new analytical flow models are required. An empirical leakage resistance/preload model is proposed to characterize the observed decrease in leakage with increasing preload. Empirically determined compression modulus and preload factor are used to correlate experimental leakage data for a wide range of seal architectures. Good agreement between measured and predicted values are observed over a range of engine pressures and seal preload.

Cai, Zhong↗

Motion Planning Algorithms for Safety and Quantum Computing Efficiency

Motion planning remains a fundamental problem in robotics. Sampling-based algorithms use randomization to allow efficient solutions to this complex problem. As mobile robots and autonomous vehicles become more prevalent in everyday life, motion planning must be applied to increasingly challenging scenarios. Safety has become a paramount concern in motion planning for ensuring robotic applications enrich human lives. To date, many motion planning techniques to increase safety in the face of uncertain and dynamic environments have been developed. This dissertation first addresses distributional safety of Rapidly-Exploring Random Trees (RRT) through our algorithm W-Safe RRT. To acknowledge distributional uncertainty and poor modeling, W-Safe RRT uses the Wasserstein metric to provide a probabilistic bound on the distributional distance between a robot and obstacles. Human-interpretable environmental agent classification allows online safety margin adaptation. We propose and analyze an integrating region method for online classification that increases actor labeling accuracy based on behavioral feature values when compared to state of the art methods. The method performs class assignments based on local maximum likelihood in a created behavioral feature-space, allowing a notion of classification uncertainty. Model-based methods with safety guarantees can quickly become computationally in tractable, especially with multiple agents, higher dimensions, and plentiful unknowns. Sampling based algorithms have been parallelized for computation with multi-core computers and GPUs. We consider the use of quantum algorithms and computers for sampling-based motion planning for the first time. Quantum computing performs operations on superpositions of states and can solve certain problems much more efficiently than classical computers, but introduces previously unseen challenges. With Quantum-RRT, we recast the motion planning problem into a database-search structure and use Quantum Amplitude Amplification to find reachable states in the database with a quadratic performance increase over classical methods. We address two error sources with this method: quantum measurement and quantum oracle errors. We then extend this method to Parallel Quantum-RRT, which uses a manager-worker architecture with multiple parallel quantum workers to increase database search efficiency. We compare algorithm architectures and characterize probabilities of multiple workers finding solutions. Lastly, we test in simulation the quantum algorithms against classical versions in a wide variety of scenarios, concluding that a similar parallelization improvement is to be found in the quantum case as was found in the parallelization of classical RRT.

97 MATHEMATICS AND COMPUTING↗

The Coronal-Dimming Footprint of a Streamer-Puff Coronal Mass Ejection: Confirmation of the Magnetic-Arch-Blowout Model

A streamer puff is a recently discovered variety of coronal mass ejection (CME) of narrow to moderate width. It (1) travels out along a streamer, transiently inflating the streamer but leaving it largely intact, and (2) occurs in step with a compact ejective flare in an outer flank of the base of the streamer. These aspects suggest the following magnetic-arch-blowout scenario for the production of these CMEs: the flare eruption expels a plasmoid that explodes up the leg of an outer loop of the arcade base of the streamer, blows out the top of this loop, and becomes the core of the CME. In this paper, we present a streamer-puff CME that produced a coronal dimming footprint. The coronal dimming, its magnetic setting, and the timing and magnetic setting of a strong compact ejective flare within the dimming footprint nicely confirm the magnetic-arch-blowout model. From these observations, together with several published cases of a trans-equatorial CME produced in tandem with an ejective flare or filament eruption that was far offset from directly under the CME, we propose that streamer-puff CMEs belong to a large class of "over-and-out" CMEs that are often much larger than streamer puffs but are similar to them in that they are produced by the blowout of a large quasi-potential magnetic arch by an ejective flare or filament eruption in one foot.

Moore, Ronald L.↗

On the Sensitivity of Atmospheric Ensembles to Cloud Microphysics in Long-Term Cloud-Resolving Model Simulations

Month-long large-scale forcing data from two field campaigns are used to drive a cloud-resolving model (CRM) and produce ensemble simulations of clouds and precipitation. Observational data are then used to evaluate the model results. To improve the model results, a new parameterization of the Bergeron process is proposed that incorporates the number concentration of ice nuclei (IN). Numerical simulations reveal that atmospheric ensembles are sensitive to IN concentration and ice crystal multiplication. Two- (2D) and three-dimensional (3D) simulations are carried out to address the sensitivity of atmospheric ensembles to model dimensionality. It is found that the ensembles with high IN concentration are more sensitive to dimensionality than those with low IN concentration. Both the analytic solutions of linear dry models and the CRM output show that there are more convective cores with stronger updrafts in 3D simulations than in 2D, which explains the differing sensitivity of the ensembles to dimensionality at different IN concentrations.

Zeng, Xiping↗

Internal structures of the Galilean satellites

Models for the interior structures of Io, Ganymede and Callisto are proposed based on recent discoveries of volcanism and high heat flow on Io, a primordial, heavily cratered surface on Callisto, and a surface modified by endogenic processes on Ganymede. The model for Io consists of a thin, high-rigidity outer shell overlying a thin, partially molten or molten layer maintained by tidal dissipation in the outer shell, which in turn surrounds a solid interior. Ganymede is modeled as an ice outer layer surrounding a shell of undifferentiated, primordial ice-silicate mixture and a rock core, with accretional heating responsible for melting the ice in an originally homogeneous ice-silicate interior. Finally, the old, heavily cratered surface of Callisto is interpreted as suggesting a primordial ice-silicate mixture with little, if any, ice-rock differentiation in the interior.

Schubert, G.↗