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“Evaluation of boundary layer cloud processes in an advanced parameterization for global models” (Final Report)
Low clouds over the ocean are a critical component of our planet’s energy budget because they emit almost as much energy as the surface while being much more reflective than the ocean, resulting in a strong net cooling effect. Despite their importance, low marine clouds remain a persistent source of uncertainty in future climate projections. This project explored how the dynamics, thermodynamics and spatial organization of low clouds is represented in a particular physical simplification, or parameterization, of small-scale air motions and cloud processes commonly employed in global atmospheric models used for short-term weather and longer-term earth system prediction. The overall goal was to develop long-term observational products to constrain numerical model representations of turbulence and cloud processes using observations from the US Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) program’s Eastern North Atlantic (ENA) site. These constraints were then used to demonstrate the type of information that can be gained from confronting simulations with the observations and we assessed the performance of a parameterization in simulating periods of low clouds at ENA. Finally, we used detailed computational fluid dynamics simulations of turbulence and cloud properties to evaluate general physical assumptions embedded in simplified representations of clouds and turbulence for global models of the atmosphere.
Performance portability study for massively parallel computational fluid dynamics application on scalable heterogeneous architectures
Patient-specific hemodynamic simulations have the possibility to greatly improve both the diagnosis and treatment of a variety of vascular diseases. Portability will enable wider adoption of computational fluid dynamics (CFD) applications in the biomedical research community and targeting to platforms ideally suited to different vascular regions. Here, we introduce a case study in performance portability that assesses (1) the ease of porting an MPI application optimized for one specific architecture to new platforms using variants of hybrid MPI+X programming models; (2) performance portability seen when simulating blood flow in three different vascular regions on diverse heterogeneous architectures; (3) model-based performance prediction for future architectures; and (4) performance scaling of the hybrid MPI+X programming on parallel heterogeneous systems. We report on the lessons learned in porting HARVEY, a massively parallel CFD application, from traditional multicore CPUs to diverse heterogeneous architectures ranging from NVIDIA/AMD GPUs to Intel MICs and Altera FPGAs.
Coupled aero-hydro-geotech real-time hybrid simulation of offshore wind turbine monopile structures
Real-time hybrid simulation (RTHS) divides a structural system into an analytical and experimental substructure. The former is based on a well-established analytical model while the latter consists of a physical model in the laboratory, for which there is not a well-established analytical model. This paper extends real-time hybrid simulation to monopile-type Offshore Wind Turbines (OWTs) to enable the investigation of their behavior considering the response of pile foundations under operational and more severe conditions. The embedded foundation and surrounding soil of the OWT are modeled physically in a soil box in the laboratory while the remaining parts of the system and loading are modeled analytically. The program OpenFAST, developed by the National Renewable Energy Laboratory (NREL), is linked to the RTHS coordinator to determine the hydrodynamic and aerodynamic loads acting on the OWT, along with modeling the dynamics of the electric power generation equipment and associated controller for the OWT. The RTHS framework along with its initial implementation and validation are described in this paper. RTHSs of a 5 MW OWT subjected to operational and more severe conditions are performed to experimentally validate the framework. The framework offers a realistic approach to investigate the behavior of OWT structures supported on monopiles. Furthermore, this approach accounts for the coupled response of the OWT structure with its foundation, while experimentally capturing the nonlinearities of the soil-foundation interaction in real-time.
Regional Representation of Wind Stakeholders' End-of-Life Behaviors and Their Impact on Wind Blade Circularity
Wind plant power has seen tremendous growth in the US and worldwide, representing the most significant renewable energy installed capacity besides hydropower. While wind power enables decarbonizing the electricity grid, the rising amount of end-of-life (EOL) wind blades - which are arduous to recycle - present a challenge for landfills if disposed of whole and a missed opportunity to recover valuable composite materials. The circular economy (CE) concept proposes strategies to rethink, reuse and recover products, components, and materials. However, transitioning to a CE implies changing how business models, supply chains, and behaviors deal with products and waste; changes arduously captured with traditional methods used to assess circularity such as life cycle assessment or material flow analysis (MFA). Here we present an agent-based model (ABM) that captures behavioral aspects impacting wind blade circularity in the US. The ABM also accounts for wind plant projects and landfills heterogeneity - a characteristic not easily included in top-down approaches such as MFA, input-output analysis, or system dynamics. Results show that recycling is divided as most recycling facilities are on the eastern side of the country, a challenge that could be alleviated by shredding blades before transportation. Recycling programs from the wind industry could also seed recycling behaviors within wind plant owners. Better yet, new blade designs could increase circularity if original equipment manufacturers accept the risks involved with the investments needed to adapt the production lines.
Deadlock prediction via generalized dependency
Deadlocks are notorious bugs in multithreaded programs, causing serious reliability issues. However, they are difficult to be fully expunged before deployment, as their appearances typically depend on specific inputs and thread schedules, which require the assistance of dynamic tools. However, existing deadlock detection tools mainly focus on locks, but cannot detect deadlocks related to condition variables. This paper presents a novel approach to fill this gap. It extends the classic lock dependency to generalized dependency by abstracting the signal for the condition variable as a special resource so that communication deadlocks can be modeled as hold-and-wait cycles as well. It further designs multiple practical mechanisms to record and analyze generalized dependencies. In the end, this paper presents the implementation of the tool, called UnHang. Experimental results on real applications show that UnHang is able to find all known deadlocks and uncover two new deadlocks. Overall, UnHang only imposes around 3% performance overhead and 8% memory overhead, making it a practical tool for the deployment environment.
Vertical Axis Wind Turbine (VAWT) with Thermoplastic Composite Blades
Rising concerns about global climate change, planet pollution and increasing use of energy have accelerated wider utilization of renewable energy sources. A recent trend in energy system development is decentralization of power generation systems. The opportunity for individuals or organizations to generate electricity locally decreases losses and part of the electricity price caused by the long-distance power transmission. Vertical axis wind turbines (VAWTs) cannot compete with traditional horizontal axis wind turbines (HAWTs) on the basis of aerodynamic performance or maximum power output generated for a given footprint. However, their ability to perform at a wide range of wind speeds, indifference to wind direction, simplicity of fabrication, transportability and maintainability make them ideal candidates for decentralized installations in urban and residential areas. The project team including Steelhead Composites (SHC), Colorado State University (CSU), National Renewable Energy Laboratory (NREL) and Arkema Inc. designed and fabricated a VAWT rotor assembly with thermoplastic composite blades using novel infusion and fabrication techniques. This full-scale VAWT rotor assembly was designed for a rated power output of 0.5-1 kW, as estimated through analytical computational fluid dynamics (CFD) methods. Those CFD simulations were combined with structural finite element analysis (FEA) to optimize the shape and composite layup of the wind blades. Much of the emphasis of this program was to characterize the recyclable thermoplastic material and composite structural design, in order to take full advantage of the material properties of such composites. Additionally, this project examined the potential of thermoplastic resin systems to transform the way VAWT rotor assemblies are joined both in the factory in in the field, by utilizing thermally welded joints to minimize field failure. The infused composite blades manufactured during this program are an excellent example of these benefits made possible by the Arkema thermoplastic resin system. This prototype blade manufacturing also provided the groundwork to inform decisions for larger scale manufacturing techniques applicable to a commercialization strategy. There is specific commercial interest for small scale VAWT’s that are competitively priced, perform to expectations, and have environmentally conscious end-of-life characteristics. Economic analysis was also conducted to compare designs and material usage, providing an estimated levelized cost of energy (LCOE) for the VAWT. The next steps for commercialization would include testing of the rotor assembly to verify predicted performance, specification of the balance of plant components (generator, inverter, etc.), and identification of a manufacturing partner with capability to scale-up production. This program has showed the potential for a commercially viable product through detailed analysis, material characterization and prototype fabrication.
Deep Underground Neutrino Experiment (DUNE) Near Detector Conceptual Design Report
The Deep Underground Neutrino Experiment (DUNE) is an international, world-class experiment aimed at exploring fundamental questions about the universe that are at the forefront of astrophysics and particle physics research. DUNE will study questions pertaining to the preponderance of matter over antimatter in the early universe, the dynamics of supernovae, the subtleties of neutrino interaction physics, and a number of beyond the Standard Model topics accessible in a powerful neutrino beam. A critical component of the DUNE physics program involves the study of changes in a powerful beam of neutrinos, i.e., neutrino oscillations, as the neutrinos propagate a long distance. The experiment consists of a near detector, sited close to the source of the beam, and a far detector, sited along the beam at a large distance. This document, the DUNE Near Detector Conceptual Design Report (CDR), describes the design of the DUNE near detector and the science program that drives the design and technology choices. The goals and requirements underlying the design, along with projected performance are given. It serves as a starting point for a more detailed design that will be described in future documents.
System and method of detecting cavitation in pumps
A system and method for detecting cavitation in pumps for fixed and variable supply frequency applications is disclosed. The system includes a controller having a processor programmed to repeatedly receive real-time operating current data from a motor driving a pump, generate a current frequency spectrum from the current data, and analyze current data within a pair of signature frequency bands of the current frequency spectrum. The processor is further programmed to repeatedly determine fault signatures as a function of the current data within the pair of signature frequency bands, repeatedly determine fault indices based on the fault signatures and a dynamic reference signature, compare the fault indices to a reference index, and identify a cavitation condition in a pump based on a comparison between the reference index and a current fault index.
HPC Molecular Simulation Tries Out a New GPU: Experiences on Early AMD Test Systems for the Frontier Supercomputer
Molecular simulation is an important tool for nu- merous efforts in physics, chemistry, and the biological sciences. Simulating molecular dynamics requires extremely rapid cal- culations to enable sufficient sampling of simulated temporal molecular processes. The Hewlett Packard Enterprise (HPE) Cray EX Frontier supercomputer installed at the Oak Ridge Leadership Computing Facility (OLCF) will provide an exascale resource for open science, and will feature graphics processing units (GPUs) from Advanced Micro Devices (AMD). The future LUMI supercomputer in Finland will be based on an HPE Cray EX platform as well. Here we test the ports of several widely used molecular dynamics packages that have each made substantial use of acceleration with NVIDIA GPUs, on Spock, the early Cray pre-Frontier testbed system at the OLCF which employs AMD GPUs. These programs are used extensively in industry for pharmaceutical and materials research, as well as academia, and are also frequently deployed on high-performance computing (HPC) systems, including national leadership HPC resources. We find that in general, performance is competitive and installation is straightforward, even at these early stages in a new GPU ecosystem. Our experiences point to an expanding arena for GPU vendors in HPC for molecular simulation.
COMPUTATION FLUID DYNAMICS ANALYSIS FOR GENERIC SMALL MODULAR REACTOR CONTAINMENT SEPARATE EFFECTS TEST
It is desirable for fourth-generation Small Modular Reactors to be passively cooled in standard and accident operations. Passive Containment Cooling Systems can reject heat from the containment structure, without using pumps or blowers. The targeted design containment structure is a large, domed, stainless steel, cylindrical vessel. In a postulated Design Basis Accident, steam will flash inside containment. Steam condensation occurs on the inner containment wall and transfers heat through the steel containment into a large body of water known as the annular reservoir (AR) surrounding the vessel serving as the ultimate heat sink. Natural circulation drives the flow in the AR and heat will be released to the environment by evaporation of water. Unique containment geometry requires a separate effects test (SET) facility for the verification and validation of the computer code and evaluation model development and assessment for reactor licensing efforts. In this study, STAR-CCM+, a computational fluid dynamics (CFD) code was used to inform the decision-making process on the design of the SET. The CFD simulation modeled, a two-phase turbulent flow with fluid film development and heat transfer for different containment geometries. The Reactor Excursion and Leak Analysis Program will also be used in a code-to-code verification against the CFD results.
AI Benchmark Democratization and Carpentry
Benchmarks are a cornerstone of modern machine learning, enabling reproducibility, comparison, and scientific progress. However, AI benchmarks are increasingly complex, requiring dynamic, AI-focused workflows. Rapid evolution in model architectures, scale, datasets, and deployment contexts makes evaluation a moving target. Large language models often memorize static benchmarks, causing a gap between benchmark results and real-world performance. Beyond traditional static benchmarks, continuous adaptive benchmarking frameworks are needed to align scientific assessment with deployment risks. This calls for skills and education in AI Benchmark Carpentry. From our experience with MLCommons, educational initiatives, and programs like the DOE's Trillion Parameter Consortium, key barriers include high resource demands, limited access to specialized hardware, lack of benchmark design expertise, and uncertainty in relating results to application domains. Current benchmarks often emphasize peak performance on top-tier hardware, offering limited guidance for diverse, real-world scenarios. Benchmarking must become dynamic, incorporating evolving models, updated data, and heterogeneous platforms while maintaining transparency, reproducibility, and interpretability. Democratization requires both technical innovation and systematic education across levels, building sustained expertise in benchmark design and use. Benchmarks should support application-relevant comparisons, enabling informed, context-sensitive decisions. Dynamic, inclusive benchmarking will ensure evaluation keeps pace with AI evolution and supports responsible, reproducible, and accessible AI deployment. Community efforts can provide a foundation for AI Benchmark Carpentry.
First Principles Nonadiabatic Excited-State Molecular Dynamics in NWChem
Computational simulation of non-adiabatic molecular dynamics is an indispensable tool for understanding complex photoinduced processes such as internal conversion, energy transfer, charge separation, and spatial localization of excitons, to name a few. Here, we report an implementation of the fewest-switches surface hopping algorithm in the NWChem computational chemistry program. Here the surface hopping method is combined with linear-response time-dependent density functional theory calculations of adiabatic excited state potential energy surfaces. To treat quantum transitions between arbitrary electronic Born{Oppenheimer states, we have implemented both numerical and analytical differentiation schemes for derivative non-adiabatic couplings. A numerical approach for the time-derivative non-adiabatic couplings together with an analytical method for calculating non-adiabatic coupling vectors is an efficient combination for surface hopping approaches. Additionally, electronic decoherence schemes and a state reassigned unavoided crossings algorithm are also implemented to improve the accuracy of the simulated dynamics and to handle trivial unavoided crossings. We apply our code to study the ultrafast decay of photoexcited benzene, including a detailed analysis of the potential energy surface, population decay time scales, and vibrational coordinates coupled to the excitation dynamics. The development presented in this work is a baseline for future implementations of more sophisticated frameworks for simulating of non-adiabatic molecular dynamics in NWChem.
Locality-Aware Scheduling for Scalable Heterogeneous Environments
Heterogeneous computing promise boost performance of scientific applications by allowing massively parallel execution of computational tasks. However, manually managing extremely heterogeneous, multi-device systems is complicated and may result in sub-optimal performance. Specifically, data management is an extremely challenging problem on multi-device systems. In this work, we introduce two locality-aware schedulers for the Minos Computing Library (MCL), an asynchronous, task-based programming model and runtime for extremely heterogeneous systems. The first scheduler implements a pure locality-aware algorithm to maximize data reuse, though it might incur in ”hot-spots” that limit system utilization. The second scheduler mitigates this drawback by dynamically targeting between locality-awareness and system utilization based on the current workload and available computing devices. Our results show that locality-awareness greatly benefit applications that exhibit data reuse, providing up to 6.9x and 7.9x over the original MCL scheduler and equivalent OpenCL implementations, respectively. Moreover, our schedulers introduce negligible overhead compared with the original MCL scheduler and achieve similar performance for applications that don’t benefit from data locality.
Operation and Dynamic Control of Hybrid Power Systems
Poster describing the planned startup process of a solid oxide gas turbine hybrid power system to be constructed at a 20 kW scale. The work is part of the ARPA-E project award to NETL under the INTEGRATE program.
Bioimaging Science Program: 2022 Principal Investigator Meetings Proceedings
The mission of the U.S. Department of Energy’s (DOE) Biological and Environmental Research (BER) program’s Bioimaging Science Program (BSP) is to understand the translation of genomic information into the mechanisms that power living cells, communities of cells, and whole organisms. The goal of BSP is to develop new imaging and measurement technologies to visualize the spatial and temporal relationships of key metabolic processes governing phenotypic expression in plants and microbes. The extended goal of dynamic imaging is to functionally connect cellular components and interdependent organisms. Information about the time and place of chemical reactions in situ can identify causal relationships between biological activators and downstream effectors. BSP held its annual PI meeting virtually February 28–March 1. Contributing investigators are convened to review progress and current state-of-the-art bioimaging research. Holding the 2022 BSP meeting as part of the broader Genomic Science Program (GSP) PI meeting allowed researchers to interact with the extended GSP community. This convergence provided a platform for networking and exchange of ideas with experts in other technologies and in target BSP application areas, helping to forge new multidisciplinary collaborations among investigators from the sister programmatic areas within BER’s Biological Systems Science Division. An important highlight of the BSP meeting was the keynote presentation by Nobel Laureate Dr. Joachim Frank on Time-Resolved Macromolecular Imaging using Cryo-EM. He discussed microfluidic mixing and fast freezing to capture nonequilibrium intermediate states during molecular binding and conformational changes. The action of molecular machines can be captured at nanometer resolution and millisecond discrimination. BSP PIs made presentations describing their research focus and progress in plenary sessions on bioimaging science and on quantum-enabled bioimaging science research projects. BSP research at universities and DOE laboratories is presented in this report. A final discussion of the BSP was organized by meeting plenary session chairs, who prepared the following Executive Summary of current BSP research, research challenges, future opportunities, and potential ideas for expanding the BSP’s impact and interactions.
Programmable simulations of molecules and materials with reconfigurable quantum processors
Simulations of quantum chemistry and quantum materials are believed to be among the most important applications of quantum information processors. However, realizing practical quantum advantage for such problems is challenging because of the prohibitive computational cost of programming typical problems into quantum hardware. Here we introduce a simulation framework for strongly correlated quantum systems represented by model spin Hamiltonians that uses reconfigurable qubit architectures to simulate real-time dynamics in a programmable way. Our approach also introduces an algorithm for extracting chemically relevant spectral properties via classical co-processing of quantum measurement results. We develop a digital–analogue simulation toolbox for efficient Hamiltonian time evolution using digital Floquet engineering and hardware-optimized multi-qubit operations to accurately realize complex spin–spin interactions. As an example, we propose an implementation based on Rydberg atom arrays. In addition, we show how detailed spectral information can be extracted from the dynamics through snapshot measurements and single-ancilla control, enabling the evaluation of excitation energies and finite-temperature susceptibilities from a single dataset. To illustrate the approach, we show how to use the method to compute key properties of a polynuclear transition-metal catalyst and two-dimensional magnetic materials.
Dynamics of Organophosphate‐Induced Structural Changes in Acetylcholinesterase Revealed by Time‐Resolved Small‐Angle X‐Ray Scattering and Inelastic Neutron Scattering
Organophosphates (OPs), the active compounds in nerve agents and insecticides such as paraoxon (POX), exert their toxic effects by irreversibly inhibiting acetylcholinesterase (AChE). Currently available antidotes for OP toxicity can reactivate AChE, but reactivation rates are slow which can lead to irreversible nervous system damage or death. We hypothesize that better antidotes with accelerated reactivation rates can be developed by understanding the structural dynamics of OP‐AChE conjugates. Previous steady‐state small‐angle X‐ray scattering (SAXS) experiments showed that POX and certain other OPs induce quaternary structural changes in human AChE (hAChE) that were reversible by oxime antidotes. To characterize the dynamics of these OP‐induced structural changes we have used time‐resolved SAXS (TR‐SAXS) and inelastic neutron scattering (INS). Stopped‐flow TR‐SAXS experiments were performed at BL‐4 at the Stanford Synchrotron Radiation Lightsource by mixing a molar excess of POX (500 μM) with hAChE (50 μM). Scattering data were collected every 20 msec during the first 1000 msec after mixing. Changes in the solution structure of hAChE during this period occurred with k obs = 0.13(±0.01) s −1 . This rate of structural change is comparable to the rate of hAChE inactivation observed using biochemical assays. INS data were collected at the Cold Neutron Chopper Spectrometer at the Spallation Neutron Source at Oakridge National Laboratory using 100 mg samples of hAChE and POX‐hAChE that were lyophilized and rehydrated in D 2 O. INS data collected at 120 K (to prevent translational motions) were used to compare the vibrational density states of native and POX‐conjugated hAChE. The POX‐conjugated hAChE exhibited an increased number of vibrational states, particularly those associated with regional motions such as loop dynamics, whereas global collective motions remained unchanged. Molecular dynamics simulations were used to simulate the vibrational spectra and identify the region(s) in hAChE that contributed to the differences in the INS experimental data. In aggregate, these studies provide experimental evidence for OP conjugate‐induced changes in hAChE dynamics that has to be considered in the design of antidotes for OP poisoning that have improved efficacy and patient outcomes. Support or Funding Information This work was supported by the CounterACT Program, National Institutes of Health Office of the Director, Grant 1U01NS083451 from NINDS, and by grants to SSRL and ORNL from the U.S. Department of Energy, and the National Institutes of Health. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .