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At least 775 records · Page 43

Shrinkage-induced deformations and creep of structural concrete: 1-year measurements and numerical prediction

Highlights: • Extensive experimental study on drying shrinkage, creep and microcracking of concrete • All specimens prepared from a single batch of ordinary-strength structural concrete • 1st year of measurements of (not only) non-uniformly drying beams with span up to 3-m • The database is downloadable from free-to-use research data repository • Modified MPS model for concrete creep used in blind prediction of all experiments The material models for creep and shrinkage operating on the material point level in FEM are usually intended for challenging complex applications and structures, where the average cross-sectional approach does not suffice. The identification of the growing number of material parameters induced by increasing model capabilities relies on very specific and narrow-oriented yet interconnected experiments which are scarce. The presented comprehensive experiments aim to provide a clearer image of the complicated interaction among the basic phenomena: drying, shrinkage, creep, and microcracking. The cornerstone of this ongoing research is a unique set of 30 partially-sealed unreinforced concrete beams with span 1.75–3.0 m subjected to drying. To minimize material variation, all specimens in this study were cast from a single batch of ordinary strength structural concrete with slag-blended binder. The resulting experimental database will be suitable both for validation and development of the constitutive models.

36 MATERIALS SCIENCE↗

Direct Observations of Field-Intensity-Dependent Dielectric Breakdown Mechanisms in TiO 2 Single Nanocrystals

One of the main challenges for next-generation electric power systems and electronics is to avoid premature dielectric breakdown in insulators and capacitors and to ensure reliable operations at higher electric fields and higher efficiencies. However, dielectric breakdown is a complex phenomenon and often involves many different processes simultaneously. Here we show distinctly different defect-related and intrinsic breakdown processes by studying individual, single crystalline TiO 2 nanoparticles using in-situ transmission electron microscopy (TEM). As the applied electric field intensity rises, rutile-to-anatase phase transition, local amorphization/melting, or ablation are identified as the corresponding breakdown processes, the field intensity thresholds of which are found to be related to the position of the intensified field and the duration of the applied bias relative to the time of charged defects accumulation. Our observations reveal an intensity-dependent dielectric response of crystalline oxides at breakdown and suggest possible routes to suppress the iniation of premature dielectric breakdown. Hence, they will aid the design and development of next generation robust and efficient solid dielectrics.

36 MATERIALS SCIENCE↗

A Cation-Tethered Flowable Polymeric Interface for Enabling Stable Deposition of Metallic Lithium

A fundamental challenge, shared across many energy storage devices, is the complexity of electrochemistry at the electrode–electrolyte interfaces that impacts the Coulombic efficiency, operational rate capability, and lifetime. Specifically, in energy-dense lithium metal batteries, the charging/discharging process results in structural heterogeneities of the metal anode, leading to battery failure by short-circuit and capacity fade. In this work, we take advantage of organic cations with lower reduction potential than lithium to build an electrically responsive polymer interface that not only adapts to morphological perturbations during electrodeposition and stripping but also modulates the lithium ion migration pathways to eliminate surface roughening. As a result, we find that this concept can enable prolonging the long-term cycling of a high-voltage lithium metal battery by at least twofold compared to bare lithium metal.

25 ENERGY STORAGE↗

Substituent Effects on Exchange Coupling and Magnetic Relaxation in 2,2'-Bipyrimidine Radical-Bridged Dilanthanide Complexes

Systematic analysis of related compounds is crucial to the design of single-molecule magnets with improved properties, yet such studies on multinuclear lanthanide complexes with strong magnetic coupling remain rare. In this work, we present the synthesis and magnetic characterization of the series of radical-bridged dilanthanide complex salts [(Cp* 2 Ln) 2 (μ-5,5'-R 2 bpym)](BPh 4 ) (Ln = Gd, Dy; R = NMe 2 (1), OEt (2), Me (3), F (4); bpym = 2,2'-bipyrimidine). Modification of the substituent on the bridging 5,5'-R 2 bpym radical anion allows the magnetic exchange coupling constant, J Gd-rad , for the gadolinium compounds in this series to be tuned over a range from -2.7 cm -1 (1) to -11.1 cm -1 (4), with electron-withdrawing or -donating substituents increasing or decreasing the strength of exchange coupling, respectively. Modulation of the exchange coupling interaction has a significant impact on the magnetic relaxation dynamics of the single-molecule magnets 1-Dy through 4-Dy, where stronger J Gd-rad for the corresponding Gd 3+ compounds is associated with larger thermal barriers to magnetic relaxation ( U eff ), open magnetic hysteresis at higher temperatures, and slower magnetic relaxation rates for through-barrier processes. Further, we derive an empirical linear correlation between the experimental U eff values for 1-Dy through 4-Dy and the magnitude of J Gd-rad for the corresponding gadolinium derivatives that provides insight into the electronic structure of these complexes. This simple model applies to other organic radical-bridged dysprosium complexes in the literature, and it establishes clear design criteria for increasing magnetic operating temperatures in radical-bridged molecules.

36 MATERIALS SCIENCE↗

Deciphering electrocatalysts with multimodal operando approaches

Here, the electrocatalytic processes of a copper catalyst during nitrate electroreduction are unveiled by correlated operando microscopy and spectroscopy. Catalysts are vital to the modern chemical industry, yet their development has largely relied on trial-and-error approaches. Optimizing catalysts requires a fundamental understanding of their structure–chemical property behaviour under operational conditions. However, operando characterization remains challenging, especially for reactions occurring in the complex and dynamic liquid environments of electrochemical systems. Over the past decade, the rapid development of in situ and operando environmental transmission electron microscopy (ETEM) and microelectromechanical system (MEMS)-based closed-cell holders, enabling environmental studies within the vacuum environment of transmission electron microscopy (TEM), has substantively advanced understanding of heterogeneous catalysis, notably for gas-phase reactions. In situ ETEM enables the direct observation of the catalyst evolution in terms of structure, morphology and chemical state at the nano-to-atomic scale, providing insights into their correlation with catalytic performance.

36 MATERIALS SCIENCE↗

Identifying chemically similar multiphase nanoprecipitates in compositionally complex non-equilibrium oxides via machine learning

Abstract Characterizing oxide nuclear fuels is difficult due to complex fission products, which result from time-evolving system chemistry and extreme operating environments. Here, we report a machine learning-enhanced approach that accelerates the characterization of spent nuclear fuels and improves the accuracy of identifying nanophase fission products and bubbles. We apply this approach to commercial, high-burnup, irradiated light-water reactor fuels, demonstrating relationships between fission product precipitates and gases. We also gain understanding of the fission versus decay pathways of precipitates across the radius of a fuel pellet. An algorithm is provided for quantifying the chemical segregation of the fission products with respect to the high-burnup structure, which enhances our ability to process large amounts of microscopy data, including approaching the atomistic-scale. This may provide a faster route for achieving physics-based fuel performance modeling.

36 MATERIALS SCIENCE↗

A multi-scale cognitive interaction model of instrument operations at the Linac Coherent Light Source

The Linac Coherent Light Source (LCLS) is the world’s first x-ray free electron laser. It is a scientific user facility operated by the SLAC National Accelerator Laboratory, at Stanford, for the U.S. Department of Energy. As beam time at LCLS is extremely valuable and limited, experimental efficiency—getting the most high quality data in the least time—is critical. Our overall project employs cognitive engineering methodologies with the goal of improving experimental efficiency and increasing scientific productivity at LCLS by refining experimental interfaces and workflows, simplifying tasks, reducing errors, and improving operator safety and stress. Here, in this study, we describe a multi-agent, multi-scale computational cognitive interaction model of instrument operations at LCLS. Our model simulates the aspects of human cognition at multiple cognitive and temporal scales, ranging from seconds to hours, and among agents playing multiple roles, including instrument operator, real time data analyst, and experiment manager. The model can roughly predict impacts stemming from proposed changes to operational interfaces and workflows. Example results demonstrate the model’s potential in guiding modifications to improve operational efficiency. We discuss the implications of our effort for cognitive engineering in complex experimental settings and outline future directions for research. The model is open source, and the videos of the supplementary material provide extensive detail.

47 OTHER INSTRUMENTATION↗

A Communication Testbed for Testing Power Electronic Agent Systems

Power electronic systems (PES) incorporate complex intra-system communication, which are of vital importance for the successful operation of these systems. This paper proposes and outlines a communication testbed that will help in the development and testing of the communications between the components of PES. It allows for the comparison and evaluation of different communication methods, such as MQTT, Modbus, or User Datagram Protocol (UDP), and for the characterization of how these communication protocols perform.

Dean, Ben↗

Automating Genetic Algorithm Mutations for Molecules Using a Masked Language Model

Inspired by the evolution of biological systems, genetic algorithms have been applied to generate solutions for optimization problems in a variety of scientific and engineering disciplines. For a given problem, a suitable genome representation must be defined along with a mutation operator to generate subsequent generations. Unlike natural systems which display a variety of complex rearrangements (e.g. mobile genetic elements), mutation for genetic algorithms commonly utilizes only random point-wise changes. Furthermore, generalizing beyond point-wise mutations poses a key difficulty as useful genome rearrangements depend on the representation and problem domain. To move beyond the limitations of manually defined point-wise changes, here we propose the use of techniques from masked language models to automatically generate mutations. As a first step, common subsequences within a given population are used to generate a vocabulary. The vocabulary is then used to tokenize each genome. A masked language model is trained on the tokenized data in order to generate possible rearrangements (i.e. mutations). In order to illustrate the proposed strategy, we use string representations of molecules and use a genetic algorithm to optimize for drug-likeness and synthesizability. Finally, our results show that moving beyond random point-wise mutations accelerates genetic algorithm optimization.

59 BASIC BIOLOGICAL SCIENCES↗

eCounter: Inline Per-IP Network Monitoring at Millisecond Resolution via eBPF

Scientific data acquisition (SciDAQ) systems are shifting from archive-based workflows to streaming paradigms, where real-time, fine-grained network monitoring becomes essential. While P4-enabled devices offer per-packet in-band observability, they require specialized switches and routers. Host-side tools like Prometheus exporters lack sufficient temporal granularity. To bridge this gap, we present eCounter, a lightweight, hardware-agnostic, inline telemetry agent built on extended Berkeley Packet Filter (eBPF). eCounter captures per-interface ingress and egress traffic, categorized by IP address and protocol, at millisecond to sub-millisecond resolution. In a 100 Gbps environment, it continuously exports up to 3,257 time-series bins per second with only 4% CPU utilization at a 35¿KiB/s data rate. We evaluate eCounter across diverse NIC MTU settings, hook types, CPU architectures and operating systems, and observed negligible impact on concurrent high-throughput streaming applications. Complexity analysis confirms that it can be readily scaled to distributed SciDAQ deployments.

Mei, Xinxin [Computational Sciences and Technology↗

ASCR@40: Four Decades of Department of Energy Leadership in Advanced Scientific Computing Research

Throughout its long history, the Office of Advanced Scientific Computing Research (ASCR) has built the critical technologies to ensure U.S. leadership in energy science and national security. It has made its parent agency, the Department of Energy (DOE) and its Office of Science, the world’s recognized leader in computational science. ASCR’s stated mission is “to discover, develop, and deploy computational and networking capabilities to analyze, model, simulate, and predict complex phenomena important to the DOE.” To accomplish this goal, ASCR oversees a large complex of computing and networking facilities and is responsible for procuring, deploying and operating high-performance computing (HPC), networking and storage resources; conducting basic research in mathematics and computer science; developing and sustaining a large body of software; and collaborating with other Office of Science programs, academia and industry. ASCR’s computational science leadership has a long history, predating even DOE’s inception. Applied mathematics and advanced computing were both elements of the Manhattan Project’s Theoretical Division. In the 1950s, DOE’s predecessor, the Atomic Energy Commission, created a mathematics program to develop and apply digital computing by supporting researchers at universities and AEC laboratories. Several organizational and name changes later, this program would grow and become ASCR.

97 MATHEMATICS AND COMPUTING↗

Development of a Framework for Data Integration, Assimilation, and Learning for Geological Carbon Sequestration (DIAL-GCS) (Final Report)

This project aimed to develop and demonstrate a Data Integration, Assimilation, and Learning framework for geologic carbon sequestration projects (DIAL-GCS). DIAL-GCS is an intelligence monitoring system (IMS) for automating GCS closed-loop management by leveraging recent developments in machine learning technologies, complex event processing (CEP), and reduced-order modeling. The safe and efficient operation of GCS repositories requires integrated monitoring to track the injected CO¬2 as it moves within a storage reservoir. GCS projects are data intensive, as a result of proliferation of digital instrumentation and smart-sensing technologies. GCS projects are also resource intensive, often requiring multidisciplinary teams performing different monitoring, verification, accounting (MVA) tasks throughout the lifecycle of a project to ensure secure containment of injected CO2. The success of GCS thus depends in a large part on our ability to access, assimilate, and analyze heterogeneous data and information sources in a timely manner. This project included a number of meaningful and necessary tasks to transform the human domain knowledge into machine-interpretable rules for automating knowledge extraction and discovery in GCS. The specific technical objectives of the proposed DIAL-GCS project were to develop an ontology-driven GCS data management module for storing, querying, and exchanging GCS data (both historic and live sensor data) from multiple sources and in heterogeneous formats. Incorporate a CEP engine for detecting abnormal situations by seamlessly combining expert knowledge, rule-based reasoning, and machine learning. Enable uncertainty quantification and predictive analytics using a combination of coupled-process modeling, AI/ML methods, and reduced-order modeling, and integrate and demonstrate the system’s capabilities with both real and simulated data. As far as we know, this is one of the first projects aimed to develop intelligent monitoring systems (IMS) targeting the GCS. Under this project, the team had developed a large number of web applications and scientific algorithms that contribute the main theme of intelligent monitoring. The team has published more than a dozen peer reviewed papers and disseminated the research results at multiple technical meetings.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Evaporation Induced Entrainment of Contaminants from Evaporating and Burning Liquids.

This interim report details model development, theory, and a literature review focusing on the evaporation induced entrainment (sub-boiling) of contaminated liquids. Entrainment from a variety of sources is the topic of DOE Handbook 3010, and this report deals more broadly with fire related airborne sources of contaminants in hazardous operations. Relatively few studies have examined sub-boiling behavior in the past, however, it can be a phenomenon that presents a fire related risk under hazardous operations. Molecular dynamics simulations are used to infer the gaseous evolution of coordinated complexes, and a model for a water/plutonium/nitrate system is deduced from the simulation results by evaluating the statistical trends of the results. Questions remain as to the chemical reactivity and longevity of entrained species. A generalized computer model capability and simple analytical model assumptions are developed for predicting the results of these and other (boiling and solid entrainment) scenarios. Verification related predictions using these models are illustrated.

36 MATERIALS SCIENCE↗

Establishing Isotopic Measurement Capabilities using Laser-Induced Breakdown Spectroscopy for the Molten Salt Reactor Campaign

Proof-of-principle H isotope ratios of aqueous aerosol systems and liquid droplets on filter paper have been measured using laser-induced breakdown spectroscopy (LIBS) with root mean square error of prediction values down to 1.9%. Molten salt reactors (MSRs) will consist of a complex chemical and radiological system consistently producing new fission products as the reactor operates. Some of these fission products and/or their daughter species will leave the salt in the reactor off-gas. Monitoring the composition of the off-gas, as well as the salt itself, is important for monitoring reactor performance, including burnup, corrosion, and the concentration of impurities. Tritium is of concern for MSRs because it will be produced from the irradiation of key salt constituents, including Li and Be. LIBS offers an avenue for in situ salt and off-gas monitoring by firing a laser onto or into the sample stream to generate a plasma. The plasma light can be monitored to measure an elemental fingerprint of the sample. Extending this analysis to include isotopic ratios offers a critical expansion of the in situ monitoring capabilities being developed. This study demonstrates the expansion of Oak Ridge National Laboratory’s LIBS capabilities to monitor isotopes and shows how simple calibrations may provide rapid semiquantitative models.

07 ISOTOPE AND RADIATION SOURCES↗

Exploring the Nature of Neutrinos with the Deep Underground Neutrino Experiment (DUNE)

The Deep Underground Neutrino Experiment (DUNE) is a next-generation experimental program designed to study the behaviour of neutrino oscillation. DUNE will utilize a neutrino beam originating at Fermilab, near Chicago, and will leverage a detector at Fermilab (Near Detector) and a detector 1300 km away in South Dakota (Far Detector), south of Saskatchewan. In the first phase of DUNE, its Far Detector will comprise of two 10,000 ton (fiducial) liquid argon (LAr) time-projection chamber (TPC) modules – powerful tracking calorimeter detectors – placed nearly a mile underground. With this large, sensitive, underground detector, DUNE aims to collect a high statistics and pure sample of neutrinos at the Far Detector. This setup also offers the potential to study non-beam physical processes via e.g. neutrinos produced in the atmosphere, supernova neutrino bursts, and/or solar neutrinos, etc. A second phase will aim to add more detector mass and expand the program. The Near Detector will consist of a LAr TPC module as well: critical to constraining systematic uncertainties in the oscillation analysis. However, this LAr TPC will have a novel design using a pixel-based readout instead of the traditional wire-based readout. This and the segmentation of the LAr TPC into multiple units are crucial in mitigating the high multiplicity of neutrino interactions expected in any readout window given its proximity to the beam. The Near Detector will feature additional components and capability beyond the LAr TPC, allowing one to deeply characterize the neutrino flux. Due to the complexity of this experimental program, several smaller-scale prototype detectors have been operating to test, validate, and improve both the technical designs and software for processing and analyzing events. By operating in charged particle test beams or neutrino beams, several of the prototypes are also capable of producing valuable results. Canadian institutions are involved in the realization of the DUNE through efforts with both the Near and Far Detectors and prototypes. DUNE is anticipated to begin operating near the end of this decade/the beginning of the next. This talk will focus on the overall DUNE program, for example its ultimate plans, status, and the efforts with prototypes.

Howard, Bruce [York U., Canada; Fermilab]↗

SCEPTRE: A Cyber-Physical Emulation Capability

Cyber-physical systems form a critical but vulnerable backbone to US critical infrastructure. Recent high-profile cyber-attacks have shown the need for increased assessment and hardening of these systems. However, such assessments and investigations into advanced technologies to harden these systems is difficult due to their operational nature. Instead, modeling of these systems is heavily leveraged. Investigation into these complex systems and their potential cascading failures requires comprehensive modeling of both the cyber and physical components of the system. This paper introduces SCEPTRE, an emulation capability to address this need.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Development of a Control Co-Design Modeling Tool for Marine Hydrokinetic Turbines: Preprint

This report describes the ongoing and planned development of the software package CT-Opt (Current/Tidal Optimization), a control co-design modeling tool for marine hydrokinetic turbines. The commercialization of these turbines has faced significant challenges due to the complex, multidisciplinary nature of their design and the extreme environmental conditions of their operation. This project aims to create a modeling tool that will enable the efficient design of robust, cost-competitive hydrokinetic turbine systems. Rather than using traditional optimization methods, CT-Opt combines multiple models across a range of fidelities to enable coupled optimization of the system design and system controller via a control co-design approach. With this method, the parameters that affect system performance are considered more comprehensively at every stage of the design process. The lowest-fidelity, frequency-domain model called by CT-Opt is RAFT (Response Amplitudes of Floating Turbines), which was originally developed by the National Renewable Energy Laboratory (NREL) to model response amplitudes of floating offshore wind turbines. The highest-fidelity, time-domain model is OpenFAST, which was developed by NREL for land-based and offshore wind turbines. As part of the CT-Opt project, new functionalities will be added to RAFT and OpenFAST to enable the accurate simulation of fixed and floating marine hydrokinetic turbines. In addition to expanding the capabilities of RAFT and OpenFAST, new midfidelity models will be developed. These models will be based on RAFT and OpenFAST and will consist of linearized, state-space models derived from the fully coupled, nonlinear OpenFAST equations and derivative function surrogate models that approximate the nonlinear system behavior. Each model will be coupled with controllers to allow control co-design methods to be applied both within models and across fidelity levels, enabling efficient system optimization.

control co-design↗

Offshore Wind Workforce Safety Standards and Training Resource

The standardization of safety training requirements for people working at sea to build and operate offshore wind energy projects, adoption of those standards, and alignment with offshore safety training curriculum development was identified as a high-priority workforce gap in the U.S. Offshore Wind Workforce Assessment (Stefek, 2022). Safety is a top priority for the offshore wind industry; however, there has been uncertainty surrounding what unique safety standards and training will be needed and how various offshore wind safety stakeholders will be involved. The scope of safety training for this resource includes workers who build and operate offshore wind energy projects at sea and defines the stakeholders in the complex ecosystem. This fact sheet aims to help reduce these uncertainties by: 1) Delineating jurisdictional lines, while clarifying roles and responsibilities amongst stakeholders; 2) Identifying key actions or partnerships that can encourage further success with safety training and workforce development.

offshore wind↗