Agile Process Improvements Initiative for ASC Sierra Code Development Teams.
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This report analyzes U.S. PV and BESS supply chains and costs in 2024, for PV module and battery technologies, structural and electrical balance of system (BOS) components, as well as PV recycling. The report concludes with an analysis of technology installation trends, government support for domestic manufacturing, manufacturing jobs, and the domestic content of PV systems installed in the United States in 2024.
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Idaho National Laboratory (INL) has developed and tested engineered sorbents to separate and capture volatile fission products such iodine (I), xenon (Xe), and krypton (Kr) from off-gas streams. As noble gases, Xe and Kr can be difficult to capture and separate. Historically, cryogenic distillation has been used to execute the separation, but this method can pose significant hazards. INL has successfully developed two sorbents for Xe and Kr capture, silver mordenite polyacrylonitrile (AgZ-PAN) and hydrogen mordenite polyacrylonitrile (HZ-PAN). Adsorption studies to date successfully separated and captured Xe from carrier gas streams, but those studies focused primarily on initial separation and capture. In addition, the ability to concentrate Xe through multiple adsorption and desorption cycles has not been studied and therefore is the focus on this presentation. Concentrating Xe during desorption is ideal to produce Xe that can be used for commercial and research applications.
Mixed polycation transition metal ferrites are known to exhibit unique and superior characteristics for structural, electrical, magnetic, and optical applications. Although a few binary transition metal ferrites are found to be suitable for electrochemical energy storage application, ternary transition metal ferrites are not investigated for asymmetric supercapacitors (ASCs). Mixed polycation oxides are expected to have increased active sites that can facilitate proton and electron transfer impacting the redox reactions. Specific crystal structure and associated lattice parameters as well as surface and morphological characteristics can also influence the energy storage properties. This study for the first time reports a novel complex polycation redox material, (Cu p Mn q Zn r ) x Fe y O z and renewable pinewood (PW) derived porous carbon (POC) as electrodes for ASC. Both (Cu p Mn q Zn r ) x Fe y O z and PW-POC are subjected to electrochemical characterization and used in ASC configuration with aqueous KOH electrolyte. It is anticipated that the Faradaic characteristics of (Cu p Mn q Zn r ) x Fe y O z will make it to serve as a cathode while PW-POC with capacitive behavior will act as anode in ASCs. Relatively higher specific capacitance of > 200 F/g is observed for the (Cu p Mn q Zn r ) x Fe y O z reference electrode and fabricated ASCs. Capacitance retention rate is tested in 10,000 cycles for the working electrodes whereas for ASC, the stability tests are performed over 100 charging-discharging cycles exhibiting relatively higher capacitance retention. (Cu p Mn q Zn r ) x Fe y O z appears to be a promising material for a supercapacitor.
Quantum computing (QC) is a rapidly maturing technology with the potential for revolutionary impacts on stockpile stewardship science and national security. Recent developments in fault-tolerant architectures have compressed vendor roadmaps, and predictions of a production-ready quantum computer by the mid-2030s are becoming increasingly credible. This strategy provides a roadmap for integrating QC into the Advanced Simulation and Computing (ASC) program by investing in four strategic focus areas: 1. Develop Capabilities in Mission-Relevant Quantum Applications: ASC will prioritize developing quantum-ready applications in mission areas that have shown significant promise for quantum advantage, including simulations of materials in extreme environments, nuclear dynamics, solving linear and nonlinear partial differential equations, and uncertainty quantification. These applications directly support stockpile stewardship science and modernization objectives. 2. Conduct R&D in Algorithms, Software, and Hardware: Sustained research into quantum algorithms, robust software tools, and quantum hardware is essential. ASC will develop efficient quantum algorithms; invest in quantum compilers, debuggers, and performance tools; and explore specialized quantum hardware tailored to NNSA’s unique requirements. 3. Engage with Vendors and Partners: Early and active collaboration with commercial quantum hardware vendors and academic partners is critical. Through testbeds, co-design agreements, and quantum demonstration facilities, ASC will influence hardware design, gain early access to emerging technologies, and ensure that quantum platforms evolve to meet mission needs. 4. Build Knowledge, Experience, and Workforce: Expanding and upskilling the quantum-trained workforce is essential to long-term success. This includes hiring, internal training, university outreach, and postdoctoral support to ensure ASC maintains the expertise required to operate, program, and integrate quantum systems as they become available. While quantum computing will never replace classical computing, it has the potential to solve certain problems with speed and accuracy that would be unachievable using any conceivable classical high-performance computing (HPC) system. By investing strategically in QC, ASC will help propel the emergent QC industry, maintain U.S. technological leadership, ensure mission readiness, and position itself to rapidly adopt quantum technologies as they mature.
Asymmetric supercapacitors (ASCs) with two dissimilar electrodes are known to exhibit relatively moderate energy and power densities. If electrodes derived from earth-abundant materials or renewable resources such as lignocellulosic biomass (LCB) are used for fabrication, energy storage systems are expected to become less expensive and more sustainable. Hybrid electrode materials have advantages such as higher surface area, better chemical stability, and superior energy density. This study reports on the synthesis of a novel hybrid electrode material containing porous carbon (POC) and copper ferrite, which is designated as POC@Cu-ferrite, and its electrochemical performance in ASC configuration. Corn stover derived hydrochar is utilized for the sol–gel synthesis of POC@Cu-ferrite hybrid material using earth-abundant Cu and Fe-based precursors. This material is characterized using X-ray diffraction (XRD), Raman spectroscopy, Brunauer–Emmett–Teller (BET) surface area analyzer, and scanning and transmission electron microscopy (SEM/TEM). As-synthesized Cu-ferrite is found to contain 89.2% CuFe 2 O 4 and 10.8% Fe 2 O 3 , whereas other phases such as Fe 3 O 4 , CuFeO 2 , and CuO are observed for the POC@Cu-ferrite. BET-specific surface area (SSA) and pore volume of POC@Cu-ferrite are observed as 1068 m 2 /g and 0.72 cm 3 /g, respectively. POC@Cu-ferrite hybrid electrode is used with POC opposite electrode to fabricate ASC, which is tested using Gamry G-300 potentiostat/galvanostat/ZRA to obtain cyclic voltammetry (CV) profiles and galvanostatic charge–discharge (GCD) plots. ASC is also prepared using Cu-ferrite and POC materials and its specific capacitance and stability are compared with ASCs prepared with POC@Cu-ferrite and POC or graphene nanoplatelets (GNPs) electrodes. POC@Cu-ferrite hybrid electrode is found to be superior with a 2-fold higher capacitance and significant electrochemical stability over 100 GCD cycles as compared to the Cu-ferrite electrode.
Abstract We use two coupled climate models, GFDL‐CM4 and GFDL‐ESM4, to investigate the physical response of the Southern Ocean to changes in surface wind stress, Antarctic meltwater, and the combined forcing of the two in a pre‐industrial control simulation. The meltwater cools the ocean surface in all regions except the Weddell Sea, where the wind stress warms the near‐surface layer. The limited sensitivity of the Weddell Sea surface layer to the meltwater is due to the spatial distribution of the meltwater fluxes, regional bathymetry, and large‐scale circulation patterns. The meltwater forcing dominates the Antarctic shelf response and the models yield strikingly different responses along West Antarctica. The disagreement is attributable to the mean‐state representation and meltwater‐driven acceleration of the Antarctic Slope Current (ASC). In CM4, the meltwater is efficiently trapped on the shelf by a well resolved, strong, and accelerating ASC which isolates the West Antarctic shelf from warm offshore waters, leading to strong subsurface cooling. In ESM4, a weaker and diffuse ASC allows more meltwater to escape to the open ocean, the West Antarctic shelf does not become isolated, and instead strong subsurface warming occurs. The CM4 results suggest a possible negative feedback mechanism that acts to limit future melting, while the ESM4 results suggest a possible positive feedback mechanism that acts to accelerate melt. Our results demonstrate the strong influence the ASC has on governing changes along the shelf, highlighting the importance of coupling interactive ice sheet models to ocean models that can resolve these dynamical processes.
This study explores the transverse momentum ( p T ) dependencies of symmetric and asymmetric correlations (SC and ASC) with one and two particles of interest in Au + Au collisions at 200 GeV. Leveraging a multiphase transport (AMPT) model, the investigation delves into the sensitivity of these correlations to the final state effects, providing valuable insights into their potential for constraining the final state effects' p T dependencies. The HIJING model is employed as a benchmark for nonflow correlations, shedding light on their impact on interpreting SC and ASC data. Moreover, the study points out that differential SC and ASC with one and two particles of interest (POIs) typically incorporate contributions from event-plane angle fluctuations. Consequently, this work highlights the significance of SC and ASC with one and two POIs as valuable tools for investigating the p T nature of the final state effects and advocates for comprehensive experimental measurements across various beam energies and system sizes to enhance understanding and provide additional constraints for theoretical models. Published by the American Physical Society 2024
The ASC program seeks to use machine learning to improve efficiencies in its stockpile stewardship mission. Moreover, there is a growing market for technologies dedicated to accelerating AI workloads. Many of these emerging architectures promise to provide savings in energy efficiency, area, and latency when compared to traditional CPUs for these types of applications — neuromorphic analog and digital technologies provide both low-power and configurable acceleration of challenging artificial intelligence (AI) algorithms. If designed into a heterogeneous system with other accelerators and conventional compute nodes, these technologies have the potential to augment the capabilities of traditional High Performance Computing (HPC) platforms [5]. This expanded computation space requires not only a new approach to physics simulation, but the ability to evaluate and analyze next-generation architectures specialized for AI/ML workloads in both traditional HPC and embedded ND applications. Developing this capability will enable ASC to understand how this hardware performs in both HPC and ND environments, improve our ability to port our applications, guide the development of computing hardware, and inform vendor interactions, leading them toward solutions that address ASC’s unique requirements.
A detailed discussion about the PTW flow-stress model has been presented, including theoretical considerations, model calibrations to experimental data, and model implementations in LANL ASC hydro-codes. The main findings are: In order to reproduce the intended behavior of the PTW model at high strain rates, the following conditions on the model parameters need to be valid: y 1 ≥ s 0 and y 2 ≥ β ; When the conditions above are not satisfied, PTW and PTW_Mod1 have slightly different behavior in the phonon-drag regime, and should be treated as different models. PTW exhibits a discontinuity above the critical strain rate. PTW_Mod1 does not show such a discontinuity but implies a different strain-rate dependence at high strain rates. Examples of this behavior include older calibrations for stainless steel and depleted uranium; In the thermal-activation regime, some flexibility was introduced in the original PTW model to allow for different rate-dependent behaviors at intermediate strain rates. Example: copper. However, many material calibrations do not require this extra flexibility, and the complexity and ambiguity of the intended behavior can be partially blamed for the inconsistent model implementations across ASC codes; The limit for the material constant p going to zero is well defined and leads to a simplified flow-stress equation, discontinuity free; Modern calibrations of the PTW parameters are done using Impala. Constraints on the PTW parameters are enforced; Implementation of the PTW model in LANL ASC hydro-codes suffered of several shortcom ings. At the time of writing, FLAG and xRAGE contain consistent and correct implemen tations of the PTW and PTW_Mod1 models. Corresponding changes to Pagosa have been suggested.
Concrete structures in nuclear installations are subject to time-dependent degradation mechanisms that can deteriorate their physical and mechanical properties, potentially exacerbating the risk of structural failure under external forces such as a seismic event. Previous research has extensively investigated the seismic response of nuclear concrete structures and the associated risk, as well as their effect on structural components safety margins. However, substantial work is still necessary to incorporate concrete aging effects into such evaluations. In fact, most models in the literature assume pristine concrete conditions and do not account for the impact of aging on the structural components’ fragility curves. This work identifies relevant time-dependent degradation mechanisms and provides simplified models to predict the the evolution of key material properties based on data from the literature. Namely, this work focuses on the aging effects of corrosion, alkali–silica reaction (ASR), and irradiation on reinforced concrete within US Department of Energy (DOE) nuclear facilities and nuclear power plants (NPP) structures. Furthermore, degradation models based on literature data are presented that define the relationship between probabilistic material properties and the concrete’s age. In this work, sampled material properties served as input for a simplified finite element model (FEM) of a critical nuclear structural system, with the output of the FEM being the seismic response for a given ground motion. The results of the FEM were then used within a probabilistic performance assessment with a statistically significant number of samples. The research presented herein addresses the detrimental effects of hazards caused by natural phenomena on deteriorated concrete elements of nuclear installations. This work directly benefits the safety analysis performed on US DOE/ National Nuclear Security Administration (NNSA) nuclear facilities located in areas prone to seismic activity. The results presented herein could aid in the improvement of DOE-STD-1020, the DOE Standard that addresses seismic risk analysis and capacity evaluation in DOE facilities. DOE-STD-1020 refers to the requirements in American Society of Civil Engineers (ASCE) 4-98, now superseded by ASCE 4-16, that shall be met in performing dynamic response analyses and generating in-structure response spectra, provided that such requirements are consistent with the requirements of ASCE/Structural Engineering Institute (SEI) 43-05. Moreover, the results presented herein could also aid in the updating of section C3.1.1. of ASCE 4-16 to account for the effects of aging on the stiffness of reinforced elements and American Concrete Institute (ACI) 349.3R-18, “Report on Evaluation and Repair of Existing Nuclear Safety-Related Concrete Structures.” Ultimately, this work can assist the risk assessment of potential lifetime extension of the existing US commercial nuclear fleet (light water reactors) and the safety analysis of the emerging advanced nuclear reactors. The proposed proof-of-concept methodology employs open-source DOE computational tools and is transferable to commercial software commonly used by engineering firms.