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The Effects of Shallow Cumulus Cloud Shape on Interactions Among Clouds and Mixing With Near-Cloud Environments
Cloud lifecycles are influenced by interactions among clouds and mixing with cloud-free environments. Cloud shapes dictate the length of cloud boundaries, which affects these interactions. This study uses a large eddy simulation to examine the relationships between the shallow cumulus cloud shapes, processes at their boundaries, and lifecycles. To characterize the shape of clouds, two metrics are newly defined: one reflects the overall horizontal cloud shape, and the other defines the cloud edge irregularity. Simulated clouds experience increased irregularity, but little changes in aspect ratio. Irregularity-driven cloud perimeter growth strongly indicates cloud splitting, with a more pronounced effect than aspect ratio-driven perimeter growth. Smaller cloud-shell gradients of properties across cloud boundaries are associated with more irregular clouds, suggesting enhanced mixing of clouds with the cloud-free environment. These findings indicate that the shallow cumulus evolution is partly driven by the irregularity of the cloud edge through lateral mixing and cloud splitting.
Phenological shifts in lake stratification under climate change
One of the most important physical characteristics driving lifecycle events in lakes is stratification. Already subtle variations in the timing of stratification onset and break-up (phenology) are known to have major ecological effects, mainly by determining the availability of light, nutrients, carbon and oxygen to organisms. Despite its ecological importance, historic and future global changes in stratification phenology are unknown. Here, we used a lake-climate model ensemble and long-term observational data, to investigate changes in lake stratification phenology across the Northern Hemisphere from 1901 to 2099. Under the high-greenhouse-gas-emission scenario, stratification will begin 22.0 ± 7.0 days earlier and end 11.3 ± 4.7 days later by the end of this century. It is very likely that this 33.3 ± 11.7 day prolongation in stratification will accelerate lake deoxygenation with subsequent effects on nutrient mineralization and phosphorus release from lake sediments. Further misalignment of lifecycle events, with possible irreversible changes for lake ecosystems, is also likely.
Examining astrophysical gas cloud collapse using an optical depth-scaled, x-ray-irradiated, carbon-foam sphere
When stellar radiation interacts with a molecular cloud, the cloud's fate depends on the strength of the incident radiation and the radiation's mean-free-path within the cloud [F. Bertoldi, Astrophys. J. 346, 735–755 (1989)]. Under the right conditions, the radiation compresses the cloud and a star formation may occur. Where and when the stellar formation occurs in the cloud's collapse are open questions. Direct observation of the complete star–cloud lifecycle is nearly impossible due to the immense timescales and distances over which the interaction occurs. Laboratory astrophysics offers a way to investigate such a system by scaling the important astrophysical parameters to the laboratory. This work describes laboratory experiments to study the radiation-driven implosion of clouds, using x rays from a laser-irradiated, thin, gold foil as a surrogate star and a carbon-foam sphere as a surrogate cloud. An optically thick system, theoretically corresponding to a star-forming regime, was selected by choice of the foam density. Gold foil and sphere motions were imaged by x-ray radiography. Radiographic images show the formation of an interface between rarefied gold and carbon plasmas, a shock moving into the sphere, and a blunting of the initial sphere's shape. Measurements show that the shock moved linearly around 64 μm/ns into the sphere, and the gold–carbon interface formed by 2 ns at the sphere edge remained stationary. The deformation of the sphere was driven by the incident radiation and not by mechanical pressures applied by gold plasma. The blunting of the sphere was likely due to the geometric reduction of flux near the sphere's poles. Higher x-ray flux near the sphere's equator caused high compression and a faster shock, which flattened the sphere. We will discuss the results and implications of our observations.
Recurrent pattern of extreme fire weather in California
Abstract Historical wildfire events in California have shown a tendency to occur every five to seven years with a rapidly increasing tendency in recent decades. This oscillation is evident in multiple historical climate records, some more than a century long, and appears to be continuing. Analysis shows that this 5–7 year oscillation is linked to a sequence of anomalous large-scale climate patterns with an eastward propagation in both the ocean and atmosphere. While warmer temperature emerges from the northern central Pacific to the west coast of California, La Niña pattern develops simultaneously, implying that the lifecycle of the El Niño-Southern Oscillation that takes multiple years to form could be a trigger. The evolving patterns of the Pacific-to-North America atmospheric teleconnection suggest the role of tropical and subtropical forcing embedded in this lifecycle. These results highlight the semi-cyclical hydrological behavior as a climate driver for wildfire variability in California.
From Reproducible Edge–Cloud Experimentation to Real-World Practice: The E2Clab Experience
Reproducibility is already difficult in distributed systems; on the computing continuum, it becomes substantially harder. Applications that span sensing devices, edge and fog resources, and cloud platforms must be evaluated across heterogeneous hardware, variable network conditions, cross-layer orchestration decisions, and long-running workflow lifecycles. We use E2Clab as a case study to examine these challenges and their implications for experimental methodology. We explain why reproducible experimentation is harder on the continuum, then revisit E2Clab as an initial response based on explicit modeling of infrastructure, workflow lifecycle, and artifacts. Lastly, we discuss how its evolution toward more realistic application settings can be understood through the lens of Translational Computer Science. We argue that reproducible continuum experimentation requires methods that are rigorous enough for research while remaining adaptable to real-world practice.
Decision-Making Under Uncertainty for a Digital Thread-Enabled Design Process
Abstract Digital thread is a data-driven architecture that links together information from all stages of the product lifecycle. Despite increasing application in manufacturing, maintenance/operations, and design related tasks, a principled formulation of analyzing the decision-making problem under uncertainty for the digital thread remains absent. The contribution of this article is to present a formulation using Bayesian statistics and decision theory. First, we address how uncertainty propagates in the product lifecycle and how the digital thread evolves based on the decisions we make and the data we collect. By using these mechanics, we explore designing over multiple product generations or iterations and provide an algorithm to solve the underlying multistage decision problem. We illustrate our method on an example structural design problem where our method can quantify and optimize different types and sequences of decisions, ranging from experimentation, manufacturing, and sensor placement/selection, to minimize total accrued costs.
RESCue Model (RESCue Experiment and Model) [SWR-24-84]
The Renewable Energy and Storage Cybersecurity Research (RESCue) project is a collaborative effort aimed at securing the rapidly growing deployment of transmission-connected hybrid renewable energy systems, consisting of a combination of wind, solar, and/or energy storage equipment, against escalating cyber threats. This project brings together major original equipment manufacturers (OEMs) of wind, solar, and energy storage, along with major asset owners and DOE National Laboratories, to collectively identify cyber threats, assess risks, and develop robust cybersecurity strategies and solutions. The development of hybrid reference architectures has provided comprehensive blueprints for the secure design and integration of hybrid renewable energy systems, accounting for their unique characteristics and interdependencies. Additionally, NREL has created a cyber-resilient design framework that integrates cybersecurity considerations from the start of the system lifecycle, ensuring security is "baked in" from the initial design phase. The research thrusts for the project included (i) development of hybrid reference architectures and (ii) a cyber-resilient design framework for hybrid energy systems. The reference architectures has provided comprehensive blueprints for the secure design and integration of hybrid renewable energy systems, accounting for their unique characteristics and interdependencies. Additionally, NREL has created a cyber-resilient design framework that integrates cybersecurity considerations from the start of the system lifecycle, ensuring security is "baked in" from the initial design phase. A demonstration experiment was developed for one of the architectures using NREL's Cyber Range resources. This experiment configuration, deployable using open-source tools, is provided here in this repository. Additional models were developed for the wind and solar architectures as well, however the configurations for only the Energy Storage scenario are provided here: https://www.nrel.gov/docs/fy24osti/89921.pdf
DEMographic MicrOSimulation (DEMOS) v2.0
DEMOS is an agent-based simulation framework used to evolve population demographic characteristics or lifecycle events such as education, marital status etc. DEMOS modules are designed to capture the interdependencies of short-term and long-term lifecycle events often influential in downstream transportation and land use modeling. An important facet of DEMOS is that it is dynamic, meaning it captures the impact of an agent's demographic characteristics in year 't' on their demographic status in year 't+1'. This has important consequences on medium- and long-term downstream modeling in different domains, such as transportation where decisions such as household vehicle transactions (i.e., buying, selling, or replacing a vehicle) depend current or past household vehicle holdings as well as household transitions. Other downstream modeling that can be enabled by DEMOS include building technology adoption or retrofit decisions, and more. DEMOS modules include: individual age progression year by year, individual mortality events, household restructuring events including marriage match-making; household birth events; individual education participation; individual labor force participation; child leaving household; household in-migration and out-migration for the region; household residence location choice and household mandatory destination choice (work and school). This version of DEMOS is tailored to be integrated with the land use simulation software UrbanSim.
Retrofit Energy Analysis and Central Thermal modeling (REACT) v1.0
REACT is a website designed to simplify the analysis and decision-making process for retrofitting existing central plant heating and cooling systems with advanced heat pump technologies. The tool evaluates the technical and economic viability of replacing traditional boilers with various options including water-to-water or air-to-water heat pumps, which can provide efficient and lower-cost heating and cooling. It allows users to compare current central plant configurations with retrofit scenarios, assessing energy consumption, life-cycle costs, and environmental impact. Retrofitting traditional boiler and chiller systems with water-to-water or air-to-water heat pumps can significantly reduce energy consumption and lower lifecycle costs. The REACT provides: User-Friendly Tools: A user friendly web interface for quick, intuitive analysis accessible to non-experts. Advanced Modeling: A Python-powered engine for detailed parametric studies, optimization, and research applications. Comprehensive Analysis: Lifecycle cost evaluation, energy consumption modeling, and environmental impact assessment. Visual Insights: A variety of plots to visualize system performance and design trade-offs. The engine for the website (REACT) bases on several Python libraries, and the website will be hosted on an ETA server.
Modeling suggests that virion production cycles within individual cells is key to understanding acute hepatitis B virus infection kinetics
Hepatitis B virus (HBV) infection kinetics in immunodeficient mice reconstituted with humanized livers from inoculation to steady state is highly dynamic despite the absence of an adaptive immune response. To recapitulate the multiphasic viral kinetic patterns, we developed an agent-based model that includes intracellular virion production cycles reflecting the cyclic nature of each individual virus lifecycle. The model fits the data well predicting an increase in production cycles initially starting with a long production cycle of 1 virion per 20 hours that gradually reaches 1 virion per hour after approximately 3–4 days before virion production increases dramatically to reach to a steady state rate of 4 virions per hour per cell. Together, modeling suggests that it is the cyclic nature of the virus lifecycle combined with an initial slow but increasing rate of HBV production from each cell that plays a role in generating the observed multiphasic HBV kinetic patterns in humanized mice.
Digital twin framework for PIP-II linac: AI-driven multi-scale modeling from ion source to 800 MeV
The PIP-II superconducting linac at Fermilab is designed to deliver multi-megawatt proton beams for neutrino physics and other high-intensity applications. To expedite commissioning and enhance operational reliability, we have developed an EPICS-based data flow framework that seamlessly integrates digital twins (DT) with physical twins (PT). These digital twins comprise high-fidelity beam dynamics models or data-driven surrogate models connected to their physical counterparts through real-time diagnostics and advanced machine-learning algorithms.Central to this framework is Linac_Gen, an accelerated simulation tool that incorporates convolutional neural networks, random forests, and genetic algorithms to provide up to a tenfold speedup in optimizing the accelerator geometry model. An EPICS translator layer ensures interoperability by efficiently mapping lattice parameters across diverse simulation platforms.Our EPICS-based framework supports multiple operational modes—monitoring, passive learning, closed-loop control, and online learning—covering the entire machine lifecycle. By leveraging HPC resources and multi-objective optimization techniques, the digital twin enables adaptive trajectory correction, real-time fault detection, and predictive modeling of beam stability. This comprehensive approach paves the way for robust, high-intensity operation and data-driven accelerator R&D at Fermilab.
Carbon Cycling, Environmental & Rural Economic Impacts of Collecting & Processing Specific Woody Feedstocks in Biofuels
Woody biomass will be an essential feedstock for a large-scale cellulosic biofuel industry. The life cycle carbon accounting for the production of biofuels from woody feedstocks is complex and has engendered significant controversy. Issues such as below ground carbon, carbon debt, varied regional forest practices, multiple parallel forest product lines, and development of realistic counterfactual scenarios all contribute to the complexity. DOE funded CORRIM to develop comprehensive and definitive lifecycle inventories and assessments on the production of fuels from woody feedstocks. CORRIM brought together expertise in forest practices, short rotation woody crops, bioconversion of woody biomass, process modeling, and life cycle assessment to successfully accomplish this goal. The CORRIM team has developed data on forest productivity, fuel usage, and fuel production for six regionally specific forest systems. These six forest systems include three current commercial systems; southern pine plantations, Douglas-fir plantations, naturally regenerated Northeastern (NE) spruce/fir, and three ‘short rotation woody crops’, poplar, eucalyptus and willow, which are at different stages of demonstration in the US. The fuel production systems include cellulosic ethanol and bio-oil based hydrocarbons. The project was successfully reviewed at the BETO Program review in March 2015, 2017, and 2019 and has resulted currently in 19 publications and reports and 35 presentations at both national and international conferences, with more in the pipeline. See publications and presentations for links to each document. Finally, and most importantly, CORRIM has gone beyond the scope of the original DOE proposal to work closely with GREET at Argonne National Laboratory (ANL) to incorporate all the life cycle data and scenario models into their modeling system. GREET is the most widely used and definitive information source for evaluating lifecycle carbon emissions for fuels. The incorporation of CORRIM data from this project guarantees the results of the research will be extensively used and widely disseminated. Technical process improvements and policy relevant accomplishments are detailed in the relevant programmatic sections in the full report including citations therein. Highlights are summarized here for easy reference.
Dilute and Dispose Cost Estimate for Equipment Installation per the LCCE
As directed in the Consolidation Appropriations Act, 2016, the National Nuclear Security Administration (NNSA) initiated the preconceptual design and development of a Lifecycle Cost Estimate for the Surplus Plutonium Disposition (SPD) Dilute and Dispose Program. Based on August 2016 Program Requirements Document and subsequent supplemental guidance, LANL prepared the Lifecycle Cost Estimate under key assumptions that meet the program’s requirements. For Dilute and Dispose, the program would disposition surplus Pu by diluting oxide produced at LANL with inhibitor materials, packaging the materials in containers, and shipping the containers to a deep geologic repository for permanent disposal. The base assumption is that LANL would disassemble pits, convert the Pu metal to oxide, and characterize and package the material for shipment to SRS, where it would be diluted prior to geologic disposal at the WIPP site in New Mexico. Another major assumption for the Dilute and Dispose option is that LANL would increase the current oxide production rate (or throughput) to 1500 kg/year, 5 times higher than the maximum annual production of ~300 Kgs executed by the ARIES Oxide Production Program at LANL. Analysis based on the ARIES program’s throughput model revealed that 15 pieces of equipment would need to be installed within PF-4 and certain facility improvements would need to be accomplished in order to meet the desired throughput levels. The additional equipment would be essentially identical to equipment already used within PF-4 for existing operations.
Cyber-Informed Engineering Implementation Guide: Version 1.0 [Slides]
This Implementation Guide describes the principles of Cyber-Informed Engineering (CIE) and outlines questions that engineering teams should consider during each phase of a system's lifecycle to effectively employ these principles. It describes what it means to engineer systems in a cyber-informed way, rather than offering a comprehensive, step-by-step process or procedure for CIE implementation. This guide complements - but does not replace - the application of cybersecurity standards or practices currently in place within an organization. Engineers and technicians that design critical energy infrastructure installations can use this Implementation Guide to integrate the 12 principles of CIE into each phase of the engineering lifecycle, from concept to retirement. The guide is aimed at system or design engineers, rather than software engineers or operational cybersecurity practitioners. The engineers who design, build, operate, and maintain the physical infrastructure are best positioned to leverage a system's engineering design to diminish the severity of cyber attacks or digital technology failures. CIE expands cybersecurity decisions into the engineering space, not by asking engineers to become cyber experts, but by calling on engineers to apply engineering tools and make engineering decisions that improve cybersecurity outcomes. CIE examines the engineering consequences that a sophisticated cyber attacker could achieve and drives engineering changes that may provide deterministic mitigations to limit or eliminate those consequences.
Digital Engineering and Cybersecurity Decision Analysis in Early Phases of SMR-Driven IES Projects
Considerable efforts are underway to ensure cybersecurity is integrated into the systems engineering lifecycle. Cyber-informed engineering and security-by-design frameworks are intended to identify and engineer out cybersecurity risks throughout the lifecycle. While these approaches are valuable for promoting the need to include cybersecurity considerations in early design phases to create more secure systems, they may not consider the entirety of digital risks. Digital risks in a digital instrumentation and control system include adversarial and unintentional risks from internal and external factors, such as human performance errors, design flaws, environmental conditions, and equipment degradation or failure. This report provides a detailed discussion on digital risk prior to describing the background and concept of operations for a small modular reactor-driven integrated energy system connected to industrial applications. The challenges of competing objectives and competing stakeholder requirements are discussed and the impacts on digital engineering, security considerations, and interdependencies are evaluated for mission-level, facility-level, and system-level decisions.
Driving Economics and Reducing Risks: The Business Case for Security-by-Design in Nuclear Power
This report provides an analysis of the financial, operational, and strategic advantages of incorporating Security-by-Design (SeBD) early in the lifecycle of nuclear power plant projects. By framing security as a foundational design element rather than a late-stage add-on, owners, vendors, and operators can reduce budget overruns, strengthen regulatory compliance, and increase revenue opportunities. The report details key lifecycle phases, highlighting the strategic imperative for organizations (including project developers, investors, vendors, and regulators) to adopt SeBD. Drawing on industry estimates, real-world case studies, and comparative cost analyses, the findings underscore that even a modest upfront investment in SeBD can yield substantial long-term returns by preventing costly retrofit activities, minimizing regulatory delays, and positioning nuclear vendors for the ability to adapt in the evolving security market. By avoiding excessive retrofit expenses and positioning security as a built-in feature rather than an afterthought, nuclear projects can protect their financial performance, enhance public trust, and secure a competitive edge in an increasingly complex global energy market. The authors advocate for SeBD’s strategic implementation, supported by established quality management methodologies, thereby promoting continuous improvement and defect avoidance. Ultimately, early SeBD integration represents a strategic investment, yielding significant returns by preventing costly retrofits and positioning nuclear projects for enhanced competitiveness and public trust.
CIE Curriculum Guide (V.2.0)
The Cyber-Informed Engineering (CIE) Curriculum Guide offers a comprehensive framework, guidance, and resources for integrating CIE into university-level engineering programs and related educational activities. The primary goal is to help educators adopt CIE principles into their teaching to produce future engineers and technicians who understand digital risks in modern engineered systems, thereby addressing the nation’s infrastructure resilience needs. This guide outlines practical integration examples, links to resources to accelerate CIE adoption, and shares insights from partner academic institutions on various implementation strategies. CIE is a framework for embedding engineered controls that mitigate the impact of cyber-attacks in any cyber-physical system used in critical energy infrastructure and other sectors. Developed by the U.S. Department of Energy’s Office of Cybersecurity, Energy Security, and Emergency Response (CESER), the National Cyber-Informed Engineering Strategy emphasizes embedding CIE into formal education, training, and credentialing. This guide supports this strategic objective by providing examples of integrating CIE concepts into engineering curricula, from class activities to new courses and certificate programs. The importance of educating cyber-informed engineers is underscored by the evolving cybersecurity threats facing engineered systems. As industrial control systems (ICS) increasingly incorporate digital technologies, the responsibility for security extends to both cyber professionals and engineers. CIE addresses critical gaps in designing and protecting physical systems with digital components against cyber risks, ensuring engineers consider digital risk throughout the engineering design lifecycle. Currently, engineering education does not routinely include cyber-informed principles, highlighting a gap in addressing modern engineering system risks. This guide advocates for updating engineering curricula to include digital risk management as a fundamental element. By doing so, future engineers will be equipped to design resilient systems that mitigate digital risks from the outset. Through this guide, engineering faculty can integrate CIE into their curricula, bridging the gap between digital risk and engineering. This approach prepares a cyber-informed workforce capable of safeguarding the cyber-physical systems crucial to national security and public welfare. By embedding CIE into education and training, institutions can produce engineers and technicians who can effectively mitigate cyber impacts throughout the engineering design lifecycle, resulting in more secure critical infrastructures.