Results for “STRUCTURAL RELIABILITY” — Page 13

DOE OSTI2022

Li 8 MnO 6 : A Novel Cathode Material with Only Anionic Redox

In Li-excess transition-metal-oxide cathode materials, anionic oxygen redox can offer high capacity and high voltages, although peroxo and superoxo species may cause oxygen loss, poor cycling performance, and capacity fading. Previous work showed that undesirable formation of peroxide and superoxide bonds is controlled to some extent by Mn substitution, and the present work uses density functional calculations to examine the reasons for this by studying the anionic redox mechanism Li 8 MnO 6 . This material is obtained by substituting Mn for Sn in Li 8 SnO 6 or for Zr in Li 8 ZrO 6 , and we also compare to previous work on those materials. The calculations predict that Li 8 MnO 6 is stable at room temperature (with a band gap of 3.19 eV as calculated HSE06 and 1.82 eV as calculated with the less reliable with PBE+U), and they elucidate the chemical and structural effects involved in the inhibition of oxygen release in this cathode. Throughout the whole delithiation process, only O 2- ions are oxidized. The directional Mn-O bonds formed from unfilled 3d orbitals effectively inhibit the formation of O-O bonds, and the layered structure is maintained even after removing 3 Li per Li 8 MnO 6 formula unit. The calculated average voltage for removal of 3 Li is 3.69 V by HSE06, and the corresponding capacity is 389 mAh/g. The high voltage of oxygen anionic redox and the high capacity result in a high energy density of 1436 Wh/kg. The Li-ion diffusion barrier for the dominant interlayer diffusion path along the c-axis is 0.57 eV by PBE+U. Finally, these results help us to understand the oxygen redox mechanism in a new lithium-rich Li 8 MnO 6 cathode material and contribute to the design of high-energy-density lithium-ion-battery cathode materials with favorable electrochemical properties based on anionic oxygen redox.

Li8MnO6↗

DOE OSTI2023

Open Circuit Switch Fault Management Method of a Multi-Phase Synchronous Buck Converter for EV Charging Application

Multi-phase synchronous buck converter (MSBC) is becoming popular for the electric vehicle (EV) charging application because of its higher efficiency, smaller passive component sizes, bidirectional power flow, and output current ripple reduction through interleaving. This converter also provides higher reliability than the traditional single phase converter since its modular structure enables fault tolerant operation. Fault management in the converter requires the detection of switch fault, shut down of the faulty phase, and reconfiguration of the PWM signals for the healthy phases to avoid circulating current and high output current ripple. In addition, it is desirable that the fault management method can be implemented using the micro-controller unit (MCU) or digital signal processor (DSP), which are widely used to control power converters. This paper presents a fault management method for detecting switch faults and reconfiguring healthy phases using a DSP. The method is validated through simulations and experiments using a commercial off-the-shelf power stack.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Assessment of Microstructure Prediction Capabilities for Powder Bed Fusion Stainless Steel 316

The Advanced Materials and Manufacturing Technologies program aims to accelerate the development, qualification, demonstration, and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy. However, the characteristic process-structure-property relationships of additive manufacturing (AM) materials pose challenges for the qualification and certification of AM nuclear components. In particular, component-scale variations in microstructure and properties can be driven by localized changes in melt pool dynamics due to how process parameters interact with different part geometries. Computational modeling tools can play a crucial role in predicting and controlling this variability. This report presents final results on process modeling tools designed to predict microstructure variability in additively manufactured stainless steel 316 parts. It details the software packages and physical modeling approaches employed to simulate an AM component within an automated process modeling workflow. Results are demonstrated through comparisons between predicted microstructures and experimental measurements across various representative processing conditions. The report concludes by discussing identified challenges and future opportunities for connecting the developed simulation workflow with mechanics simulations for prediction of part performance.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Studying the SBND Cathode Structure

The Short-Baseline Near Detector (SBND) is a Liquid Argon Time Projection Chamber (LArTPC) located at Fermilab. It utilizes electrons ionized by passing particles inside the detector to create 3D reconstructions of interactions. This is achieved by drifting ionized electrons towards the instrumented wire planes. Structurally, the cathode can be mapped using cosmic ray muons by using information of their trajectories and their timing. This study shows that the cathode has rich structure. Though preliminary, this work shows evidence of non-negligible effects and warrants further investigation of these structures which could lead to improved detector simulations and more reliable event reconstructions.

Cataldo, Aedan [Notre Dame U.]↗

DOE OSTI2024

Submerged Fatigue Testing of Marine Energy Advanced Materials

Marine energy structures are typically made of advanced composite materials and are subjected to extreme ocean environments in service. In extreme ocean environments, seawater currents and waves load structures repeatedly, which cause two environmental conditions: water intrusion and mechanical fatigue. In prior research, the two environmental conditions were applied sequentially, where composite specimens were aged and then mechanically tested. To understand the combined effects of dynamic loading and water intrusion on composite materials, the present study involves the static and fatigue four-point bend testing of composite coupons in a water tank. The water tank was designed and built to fit either a 100 kN or a 250 kN load frame. Flexural strength value, cycles to failure, and failure mode results from submerged fatigue testing will be used to inform marine energy structure designs. The coupon-scale test method will be used to scale up to and inform methods for subsequent subcomponent testing and standards development. The benefits of designing marine energy structures to informed standards are decreased lifetime costs and increased reliability and energy production, ultimately leading to a sustainable and low-carbon energy system.

composite materials↗

DOE OSTI2024

Submerged Fatigue Testing of Marine Energy Advanced Materials

Marine energy structures are typically made of advanced composite materials and are subjected to extreme ocean environments in service. In extreme ocean environments, seawater currents and waves load structures repeatedly, which cause two environmental conditions: water intrusion and mechanical fatigue. In prior research, the two environmental conditions were applied sequentially, where composite specimens were aged and then mechanically tested. To understand the combined effects of dynamic loading and water intrusion on composite materials, the present study involves the static and fatigue four-point bend testing of composite coupons in a water tank. The water tank was designed and built to fit either a 100 kN or a 250 kN load frame. Flexural strength value, cycles to failure, and failure mode results from submerged fatigue testing will be used to inform marine energy structure designs. The coupon-scale test method will be used to scale up to and inform methods for subsequent subcomponent testing and standards development. Finally, the benefits of designing marine energy structures to informed standards are decreased lifetime costs and increased reliability and energy production, ultimately leading to a sustainable and low-carbon energy system.

13 HYDRO ENERGY↗

DOE OSTI2024

Submerged Fatigue Testing of Marine Energy Advanced Materials: Preprint

Marine energy structures are typically made of advanced composite materials and are subjected to extreme ocean environments in service. In extreme ocean environments, seawater currents and waves load structures repeatedly, which cause two environmental conditions: water intrusion and mechanical fatigue. In prior research, the two environmental conditions were applied sequentially, where composite specimens were aged and then mechanically tested. To understand the combined effects of dynamic loading and water intrusion on composite materials, the present study involves the static and fatigue four-point bend testing of composite coupons in a water tank. The water tank was designed and built to fit either a 100 kN or a 250 kN load frame. Flexural strength value, cycles to failure, and failure mode results from submerged fatigue testing will be used to inform marine energy structure designs. The coupon-scale test method will be used to scale up to and inform methods for subsequent subcomponent testing and standards development. The benefits of designing marine energy structures to informed standards are decreased lifetime costs and increased reliability and energy production, ultimately leading to a sustainable and low-carbon energy system.

composite materials↗

DOE OSTI2024

Submerged Fatigue Testing of Marine Energy Advanced Materials

Marine energy structures are typically made of advanced composite materials and are subjected to extreme ocean environments in service. In extreme ocean environments, seawater currents and waves load structures repeatedly, which cause two environmental conditions: water intrusion and mechanical fatigue. In prior research, the two environmental conditions were applied sequentially, where composite specimens were aged and then mechanically tested. To understand the combined effects of dynamic loading and water intrusion on composite materials, the present study involves the static and fatigue four-point bend testing of composite coupons in a water tank. The water tank was designed and built to fit either a 100 kN or a 250 kN load frame. Flexural strength value, cycles to failure, and failure mode results from submerged fatigue testing will be used to inform marine energy structure designs. The coupon-scale test method will be used to scale up to and inform methods for subsequent subcomponent testing and standards development. The benefits of designing marine energy structures to informed standards are decreased lifetime costs and increased reliability and energy production, ultimately leading to a sustainable and low-carbon energy system.

composite materials↗

DOE OSTI2024

Bill Savings vs. Backup Power: Evaluating operational tradeoffs for home solar+storage systems [Slides]

This study explores tradeoffs between the use of home solar+storage systems for backup power versus day-to-day utility bill savings. The study focuses specifically on the “reserve setting” available with most home battery storage systems, which allow the customer to maintain some minimum level of storage in reserve in case of an unforeseen power interruption. The more capacity that is held in reserve, the greater the customer’s ability to ride-through possible power interruptions, but less capacity is then available to manage utility bills on a day-to-day basis. This study evaluates this operational tradeoff across a diverse set of locations and residential electricity tariff structures, relying on Berkeley Lab’s PRESTO model to stochastically simulate power interruption events, and exploring a range of sensitivities, including variations in customer value of lost load (VoLL), interruption frequency, and other key drivers. The results show that, in most circumstances, the opportunity cost of holding storage capacity in reserve, in terms of foregone bill saving, tends to outweigh any gains in reliability value associated with mitigated power interruptions. This finding is robust across tariff structures and across most of the sensitivities considered, including those related to rate level, customer load level, and storage sizing. There are a limited set of circumstances where raising the reserve setting improves the overall customer value (comprised of bill savings plus reliability value). Specifically, that exception occurs when all of the following conditions apply: (a) the customer resides in a location with exceptionally poor reliability, (b) the customer has exceptionally high VoLL; (c) the customer is on a net billing rate or on a TOU rate that allows grid discharging but not grid charging; and (d), depending on the location, the price arbitrage differential on that rate is relatively small. In all other circumstances analyzed, total customer value declines with reserve level.

14 SOLAR ENERGY↗

DOE OSTI2024

Can Wholesale Electricity Markets Achieve Resource Adequacy and High Clean Energy Generation Targets in the Presence of Self-Interested Actors?

Wholesale electricity markets are intended to incentivize system generation investments and operations outcomes that meet evolving system needs. In this work, we evaluate the effectiveness of wholesale market structures, rules and policies in achieving system resource adequacy (RA) and clean energy targets in the presence of self-interested generation investors using the Electricity Markets and Investment Suite Agent-based Simulation (EMIS-AS) model. Results highlight that both capacity markets and operating reserve demand curves (ORDCs) can help achieve a reliable system but with different RA compliance timelines and distribution of generation technologies. Structures with capacity markets tend to favor more capital-intensive peaking technologies while reducing wind and solar build-outs due to suppressed energy and clean energy market prices, particularly in the absence of strong clean energy targets. Conversely, ORDCs improve the commitment of available generation units, but this comes at the expense of higher system costs and renewable generation curtailment. We also find that well-calibrated static capacity demand curves can yield similar reliability and total cost compared to capacity market demand curves informed dynamically by resource adequacy while also yielding stable annual capacity prices. Different approaches to formulating ORDC curves can also yield key trade-offs, namely that a more efficient treatment of storage chronology results in lower ORDC curves and prices, yielding less investment and cost but at the expense of reliability. Finally, the effectiveness of wholesale electricity markets in practically achieving very high clean energy generation targets highly depends on the cost-competitiveness of clean energy technologies that can support critical balancing needs across multiple timescales.

capacity expansion↗

DOE OSTI2024

Wholesale Electricity Markets and Resource Adequacy with High Clean Energy Generation Targets

Wholesale electricity markets are intended to incentivize system generation investments and operations outcomes that meet evolving system needs. In this work, we evaluate the effectiveness of wholesale market structures, rules and policies in achieving system resource adequacy (RA) and clean energy targets in the presence of self-interested generation investors using the Electricity Markets and Investment Suite Agent-based Simulation (EMIS-AS) model. Results highlight that both capacity markets and operating reserve demand curves (ORDCs) can help achieve a reliable system but with different RA compliance timelines and distribution of generation technologies. Structures with capacity markets tend to favor more capital-intensive peaking technologies while reducing wind and solar build-outs due to suppressed energy and clean energy market prices, particularly in the absence of strong clean energy targets. Conversely, ORDCs improve the commitment of available generation units, but this comes at the expense of higher system costs and renewable generation curtailment. We also find that well-calibrated static capacity demand curves can yield similar reliability and total cost compared to capacity market demand curves informed dynamically by resource adequacy while also yielding stable annual capacity prices. Different approaches to formulating ORDC curves can also yield key trade-offs, namely that a more efficient treatment of storage chronology results in lower ORDC curves and prices, yielding less investment and cost but at the expense of reliability. Finally, the effectiveness of wholesale electricity markets in practically achieving very high clean energy generation targets highly depends on the cost-competitiveness of clean energy technologies that can support critical balancing needs across multiple timescales.

capacity expansion↗

DOE OSTI2024

Wholesale Electricity Market Design to Support Resource Adequacy

Wholesale electricity markets are intended to incentivize system generation investments and operations outcomes that meet evolving system needs. In this work, we evaluate the effectiveness of wholesale market structures, rules and policies in achieving system resource adequacy (RA) and clean energy targets in the presence of self-interested generation investors using the Electricity Markets and Investment Suite Agent-based Simulation (EMIS-AS) model. Results highlight that both capacity markets and operating reserve demand curves (ORDCs) can help achieve a reliable system but with different RA compliance timelines and distribution of generation technologies. Structures with capacity markets tend to favor more capital-intensive peaking technologies while reducing wind and solar build-outs due to suppressed energy and clean energy market prices, particularly in the absence of strong clean energy targets. Conversely, ORDCs improve the commitment of available generation units, but this comes at the expense of higher system costs and renewable generation curtailment. We also find that well-calibrated static capacity demand curves can yield similar reliability and total cost compared to capacity market demand curves informed dynamically by resource adequacy while also yielding stable annual capacity prices. Different approaches to formulating ORDC curves can also yield key trade-offs, namely that a more efficient treatment of storage chronology results in lower ORDC curves and prices, yielding less investment and cost but at the expense of reliability. Finally, the effectiveness of wholesale electricity markets in practically achieving very high clean energy generation targets highly depends on the cost-competitiveness of clean energy technologies that can support critical balancing needs across multiple timescales.

agent based modeling↗

DOE OSTI2023

Statement of Work: Toward AI-driven additive manufacturing for metal-ceramic composite structures

The project scope is to investigate the compatibility of various ceramic and metal powder composite feedstock development, implement AI algorithms for in-situ monitoring and parameter optimization of binder jet 3D printing to achieve reliable and robust metal/ceramic and/or ceramic/ceramic composite components, and create a generative design framework for heterogeneous composite structures incorporating metals and ceramic-based materials to achieve specific mechanical properties. Funded is the effort and travel by the faculty advisor at University of California Berkeley in support of the work of their students and the related collaborative research and development effort.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

Developing reliable machine learning interatomic potential for Fe–Cr–Ni austenitic alloys

Gaining atomistic understanding of mechanical behavior of heat-resistant structural materials such as Fe–Cr–Ni-based alloys requires an approach with an accuracy close to density functional theory (DFT) that considers the intrinsic properties of the bulk lattice and important defects such as stacking faults, grain boundaries, and surfaces. This work aims to develop reliable machine learning interatomic potential (MLIAP) at cross-scale for Fe–Cr–Ni ternary alloys with a focus on the face-centered-cubic (fcc) solid solution structure. Leveraging the advantages of moment tensor potentials, which typically necessitate a relatively small training dataset and enable rapid calculations using the large-scale atomic/molecular massively parallel simulator package, we ensure the stability and accuracy of the trained potentials. Important defects such as stacking faults, grain boundaries, and surfaces for wide-range compositions are investigated. Structural, thermal, elastic, and defect properties are determined from molecular dynamics simulations comprising several thousand atoms, generated via canonical Monte Carlo simulations guided by the trained potential. The trained potential allows efficient atomic simulations of structural, thermal, and mechanical properties of fcc Fe–Cr–Ni solid solution alloys as a function of composition and temperature. Therefore, the MLIAP approach represents a major advancement from DFT calculations that are limited to small simulation sizes and traditional molecular dynamics simulations using relatively low accuracy potentials. Furthermore, this work outlines a practical foundation for further investigating the structural evolution and mechanical behavior of austenitic stainless steel and nickel-based alloys in a wide array of applications in extreme environments.

Crystal structure↗

DOE OSTI2022

Exploring Critical Synthetic Parameters for Nanoscale ε-Fe 2 O 3 and Their Influence on Magnetic Behaviors

An intermediate polymorph of iron oxide, ε-Fe 2 O 3 , has attracted significant attention due to its giant coercive field ( H c ) and potential applications in high-frequency millimeter-wave absorption and high-density magnetic recording. However, the fabrication of ε-Fe 2 O 3 with high phase purity is still a challenge due to complicated synthetic procedures and a large variety of reaction parameters. In this study, we have identified critical reaction parameters to improve the phase purity of ε-Fe 2 O 3 , and the effects of all possible reaction parameters have been tested through systematic studies. A combination of structural and magnetic characterization techniques provides us with an accurate and reliable phase purity analysis of the ε-Fe 2 O 3 phase. Specifically, we observed that (1) the reaction temperature and time and (2) the addition of Ba are critical parameters to improve the phase purity. We identified the optimal conditions that maximize the coercivity and phase purity, giving insight into the effects of each parameter on the γ- to ε- to α-phase-transition pathway. We obtained nearly single-phase ε-Fe 2 O 3 (~87 wt % with ~13 wt % α-phase) with a large coercivity of H c = 20.6 kOe, enabling us to obtain pure ε-Fe 2 O 3 by a simple magnetic separation protocol, and tuned the H c of the ε-Fe 2 O 3 nanoparticles in the range of 4.0–20.6 kOe by controlling the reaction parameters. Furthermore, the structural properties of the resulting ε-Fe 2 O 3 nanoparticles are confirmed by characterizing their chemical and magnetic properties using X-ray absorption spectroscopy and X-ray magnetic circular dichroism measurements.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Networked Microgrid Energy Management Considering Ownership and Control Structures: A Comparison

With the growing deployment of microgrids, networked microgrids have emerged for their additional advantages of economy, reliability and resilience by coordinating the operation of multiple microgrids. As microgrids are operated with different ownership, objectives and functionalities, the formed networked microgrids show characteristics of mixed ownership, inconsistent objectives and various functionalities. To enable the coordinated operation of networked microgrids, three control structures, i.e., centralized, distributed and decentralized, have been constructed in the literature. However, the data sharing enabling these different paradigms and the resulted value propositions are not well defined, leading to poor resource management and resilience, etc. To solve this issue, a complete comparison of networked microgrid energy management under centralized, distributed and decentralized structures are performed. As a novel contribution, the required minimum data exchange of networked microgrid energy management under three control structures are identified, respectively. The value propositions are calculated and compared against each other by the results of case studies.

control structures↗

DOE OSTI2022

Asynchronous Reciprocal Coupling of Martini 2.2 Coarse-Grained and CHARMM36 All-Atom Simulations in an Automated Multiscale Framework

The appeal of multiscale modeling approaches is predicated on the promise of combinatorial synergy. However, this promise can only be realized when distinct scales are combined with reciprocal consistency. Here, we consider multiscale molecular dynamics (MD) simulations that combine the accuracy and macromolecular flexibility accessible to fixed-charge all-atom (AA) representations with the sampling speed accessible to reductive, coarse-grained (CG) representations. AA-to-CG conversions are relatively straightforward because deterministic routines with unique outcomes are achievable. Conversely, CG-to-AA conversions have many solutions due to a surge in the number of degrees of freedom. While automated tools for biomolecular CG-to-AA transformation exist, we find that one popular option, called Backward, is prone to stochastic failure and the AA models that it does generate frequently have compromised protein structure and incorrect stereochemistry. Although these shortcomings can likely be circumvented by human intervention in isolated instances, automated multiscale coupling requires reliable and robust scale conversion. In this work, we detail an extension to Multiscale Machine-learned Modeling Infrastructure (MuMMI), including an improved CG-to-AA conversion tool called sinceCG. This tool is reliable (~98% weakly correlated repeat success rate), automatable (no unrecoverable hangs), and yields AA models that generally preserve protein secondary structure and maintain correct stereochemistry. We describe how the MuMMI framework identifies CG system configurations of interest, converts them to AA representations, and simulates them at the AA scale while on-the-fly analyses provide feedback to update CG parameters. Application to systems containing the peripheral membrane protein RAS and proximal components of RAF kinase on complex eight-component lipid bilayers with ~1.5 million atoms is discussed in the context of MuMMI.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Magnetism in EuAlSi and the Eu 1−𝑥 ⁢Sr 𝑥 ⁢ AlSi solid solution solid solution

The magnetic properties of EuAlSi, a compound comprising a honeycomb lattice of Al/Si atoms and a triangular lattice of Eu atoms, are presented. By means of single-crystal x-ray diffraction, we find that EuAlSi crystallizes in an AlB 2 -type structure with space group 𝑃⁢6/mmm and unit cell parameters 𝑎 = 4.2229⁢ (10) ⁢Å and 𝑐 = 4.5268 ⁢(12)⁢ Å. Our magnetic measurements indicate that EuAlSi is a soft ferromagnetic material with 𝑇 Curie = 25.8 K. The susceptibility follows the Curie-Weiss law at high temperatures, which allowed us to determine the paramagnetic Curie temperature 𝜃 𝑃 = 36.2 ⁢(1) ⁢K and an effective magnetic moment 𝜇 eff = 8.07 ⁢(1)⁢ µ 𝐵 /Eu. This value is in agreement with the theoretical value of 7.9 µ 𝐵 for Eu 2+ free ion. Moreover, we have prepared the Eu 1−𝑥 ⁢Sr 𝑥 ⁢ AlSi solid solution, where the atoms in the triangular lattice were systematically exchanged, in order to study the evolution of the collective quantum properties from the ferromagnetic EuAlSi toward the superconducting SrAlSi. Across the Eu 1−𝑥 ⁢Sr 𝑥 AlSi solid solution, the unit cell parameters change linearly, following Vegard’s law, and making the system reliable for studying composition dependence of the interplay between the crystal structure and physical properties. As the Sr content increases, i.e., 𝑥 increases, we note a consistent reduction of 𝜇 eff and 𝑇 Curie . Long-range magnetic order in Eu 1−𝑥 ⁢Sr 𝑥 ⁢ AlSi persists up to 𝑥 = 0.95, whereas superconductivity is only observed for samples with 𝑥 > 0.97.

Walicka, Dorota I. [University of Geneva (Switzerl↗