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At least 361 records · Page 20

Parallel-vector computation for CSI-design code

Computational aspects of Control-Structure Interaction (CSI) DESIGN code is reviewed. Numerical intensive computation portions of CSI-DESIGN code were identified. Improvements in computational speed for the CSI-DESIGN code can be achieved by exploiting parallel and vector capabilities offered by modern computers, such as the Alliant, Convex, Cray-2, and Cray-YMP. Four options to generate the coefficient stiffness matrix and to solve the system of linear, simultaneous equations are currently available in the CSI-DESIGN code. A preprocessor to use RCM (Reverse Cuthill-Mackee) algorithm for bandwidth minimization was also developed for the CSI-DESIGN code. Preliminary results obtained by solving a small-scale, 97 node CSI finite element model (for eigensolution) have indicated that this new CSI-DESIGN code is 5 to 6 times faster (using 1 Alliant processor) than the old version of CSI-DESIGN code. This speed-up was achieved due to the RCM algorithm and the use of a new skyline solver. Efforts are underway to further improve the vector speed for CSI-DESIGN code, to evaluate its performance on a larger scale CSI model (such as phase zero CSI model) to make the code run efficiently on multiprocessor, parallel computer environment, and to make the code portable among different parallel computers available at NASA LaRC, such as Alliant, Convex, and Cray computers.

Nguyen, Duc T.↗

LANL ASC FY23 L2 Milestone Description and Completion Criteria [Slides]

In early 2021, the ASC Program decided that Ristra should provide a production code (Moya) for LANL’s mission in the Low Energy-Density Physics application space. At the same time, Ristra should design an environment for rapid development of new codes that can answer new questions on new hardware. We started FY22 by expanding upon our R&D efforts of high-order DG methods for hydrodynamics; Technical & staffing challenges caused us to abandon this for a traditional FV SGH approach, but leveraging modern techniques. Significant changes in FleCSI (v1.4→2.x) have us writing code anew, in a co-design effort with the FleCSI and FleCSI specialization projects.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Update on the Thermal Hydraulic Investigations of a Horizontal Dry Cask Simulator

The thermal performance of commercial spent nuclear fuel dry storage casks is evaluated through detailed numerical analysis. These modeling efforts are completed by the vendor to demonstrate performance and regulatory compliance. The calculations are then independently verified by the Nuclear Regulatory Commission (NRC). Canistered dry storage cask systems rely on ventilation between the inner canister and the overpack to convect heat away from the canister to the surrounding environment for both horizontal and vertical configurations. Recent advances in dry storage cask designs have significantly increased the maximum thermal load allowed in a canister in part by increasing the efficiency of internal conduction pathways and by increasing the internal convection through greater canister helium pressure. Carefully measured data sets generated from testing of full-sized casks or smaller cask analogs are widely recognized as vital for validating these models. While several testing programs have been previously conducted, these earlier validation studies did not integrate all the physics or components important in a modern, horizontal dry cask system. The purpose of the present investigation is to produce data sets that can be used to benchmark the codes and best practices presently used to determine cladding temperatures and induced cooling air flows in modern horizontal dry storage systems. The horizontal dry cask simulator (HDCS) has been designed to generate this benchmark data and add to the existing knowledge base. The objective of the HDCS investigation is to capture the dominant physics of a commercial dry storage system in a well-characterized test apparatus for any given set of operational parameters. The close coupling between the thermal response of the canister system and the resulting induced cooling air flow rate is of particular importance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Non-intrusive nonlinear model reduction via machine learning approximations to low-dimensional operators

Abstract Although projection-based reduced-order models (ROMs) for parameterized nonlinear dynamical systems have demonstrated exciting results across a range of applications, their broad adoption has been limited by their intrusivity: implementing such a reduced-order model typically requires significant modifications to the underlying simulation code. To address this, we propose a method that enables traditionally intrusive reduced-order models to be accurately approximated in a non-intrusive manner. Specifically, the approach approximates the low-dimensional operators associated with projection-based reduced-order models (ROMs) using modern machine-learning regression techniques. The only requirement of the simulation code is the ability to export the velocity given the state and parameters; this functionality is used to train the approximated low-dimensional operators. In addition to enabling nonintrusivity, we demonstrate that the approach also leads to very low computational complexity, achieving up to $$10^3{\times }$$ 10 3 × in run time. We demonstrate the effectiveness of the proposed technique on two types of PDEs. The domain of applications include both parabolic and hyperbolic PDEs, regardless of the dimension of full-order models (FOMs).

42 ENGINEERING↗

Quantum Package 2.0: An Open-Source Determinant-Driven Suite of Programs

Quantum chemistry is a discipline which relies heavily on very expensive numerical computations. The scaling of correlated wave function methods lies, in their standard implementation, between O(N-5) and O(e(N)), where N is proportional to the system size. Therefore, performing accurate calculations on chemically meaningful systems requires (i) approximations that can lower the computational scaling and (ii) efficient implementations that take advantage of modern massively parallel architectures. QUANTUM PACKAGE is an open-source programming environment for quantum chemistry specially designed for wave function methods. Its main goal is the development of determinant-driven selected configuration interaction (sCI) methods and multireference second-order perturbation theory (PT2). The determinant-driven framework allows the programmer to include any arbitrary set of determinants in the reference space, hence providing greater methodological freedom. The sCI method implemented in QUANTUM PACKAGE is based on the CIPSI (Configuration Interaction using a Perturbative Selection made Iteratively) algorithm which complements the variational sCI energy with a PT2 correction. Additional external plugins have been recently added to perform calculations with multireference coupled cluster theory and range-separated density-functional theory. All the programs are developed with the IRPF90 code generator, which simplifies collaborative work and the development of new features. QUANTUM PACKAGE strives to allow easy implementation and experimentation of new methods, while making parallel computation as simple and efficient as possible on modern supercomputer architectures. Currently, the code enables, routinely, to realize runs on roughly 2 000 CPU cores, with tens of millions of determinants in the reference space. Moreover, we have been able to push up to 12 288 cores in order to test its parallel efficiency. In the present manuscript, we also introduce some key new developments: (i) a renormalized second-order perturbative correction for efficient extrapolation to the full CI limit and (ii) a stochastic version of the CIPSI selection performed simultaneously to the PT2 calculation at no extra cost.

Garniron, Yann↗

Machine Learning Classical Interatomic Potentials for Molecular Dynamics from First-Principles Training Data

The ever-increasing power of modern super-computers, along with the availability of highly scalable atomistic simulation codes, has begun to revolutionize predictive modeling of materials. In particular, molecular dynamics (MD) has led to breakthrough advances in diverse fields, including tribology, catalysis, sensing, and nanoparticle self-assembly. Furthermore, recent integration of MD simulations with X-ray characterization has demonstrated promise in real-time 3-D characterization of materials on the atomic scale. The popularity of MD is driven by its applicability at disparate length/time scales, ranging from ab initio MD (hundreds of atoms and tens of picoseconds) to all-atom classical MD (millions of atoms over microseconds), and coarse-grained (CG) models (micrometers and tens of microseconds). Nevertheless, a substantial gap persists between AIMD, which is highly accurate but restricted to extremely small sizes, and those based on classical force fields (atomistic and CG) with limited accuracy but access to larger length/time scales. The accuracy and predictive power of classical MD simulations is dictated by the empirical force fields, and their capability to capture the relevant physics. Here, we discuss some of our recent work on the use of machine learning (ML) to combine the accuracy and flexibility of electronic structure calculations with the speed of classical potentials. Our ML framework attempts to bridge the significant gulf that exists between the handful of research groups that develop new interatomic potential models (often requiring several years of effort), and the increasingly large user community from academia and industry that applies these models. Our data-driven approach represents significant departure from the status quo and involves several steps including generation and manipulation of extensive training data sets through electronic structure calculations, defining novel potential functional forms, employing state-of-the-art ML algorithms to formulate highly optimized training procedures, and subsequently developing user-friendly workflow tools integrating these algorithms on high-performance computers (HPCs). Our ML approach shows marked success in developing force fields for a wide range of materials from metals, oxides, nitrides, and heterointerfaces to two-dimensional (2D) materials.

Chan, Henry↗

RELAP-7 Pressurizer Component Development Updates

RELAP-7 is a nuclear systems safety analysis code being developed at the Idaho National Laboratory (INL). RELAP-7 development began in 2011 to support the Risk Informed Safety Margins Characterization (RISMC) Pathway of the Light Water Reactor Sustainability (LWRS) program. The overall design goal of RELAP-7 is to take advantage of the previous thirty years of advancements in computer architecture, software design, numerical methods, and physical models in order to provide capabilities needed for the RISMC methodology and to support nuclear power safety analysis. The code is being developed based on Idaho National Laboratory’s modern scientific software development framework – MOOSE (the Multi-Physics Object-Oriented Simulation Environment). The initial development goal of the RELAP-7 approach focused primarily on the development of an implicit algorithm capable of strong (nonlinear) coupling of the dependent hydrodynamic variables contained in the 1-D/2-D flow models with the various 0-D system reactor components that compose various boiling water reactor (BWR) and pressurized water reactor nuclear power plants (NPPs). As part of the efforts to expand the capability for PWR simulation, an equilibrium single-region pressurizer model has been implemented in RELAP-7. The pressurizer component can simulate pressure and water level change through insurge, spray, and heating processes. Two simple tests – one for insurge process and another for outsurge process – have been reported to demonstrate and verify the functions of the pressurizer model. The typical single-phase PWR system model presented in the first RELAP-7 milestone report has been updated, as part of system level test for the new pressurizer model. The updated PWR system model with the pressurizer component can be used for more realistic transient simulations. The addition of the equilibrium single-region pressurizer model represents the first step of developing a suite of pressurizer models with different levels of fidelities. Non-equilibrium two-region two-zone model and non-equilibrium five-region three zone model will be implemented in the near future. Cross comparison and validation will be pursued when higher fidelity pressurizer models are completed.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Acceleration of the particle-in-cell code Osiris with graphics processing units

Fully relativistic particle-in-cell (PIC) simulations are crucial for advancing our knowledge of plasma physics. Modern supercomputers based on graphics processing units (GPUs) offer the potential to perform PIC simulations of unprecedented scale, but require robust and feature-rich codes that can fully leverage their computational resources. In this work, this demand is addressed by adding GPU acceleration to the PIC code Osiris. An overview of the algorithm, which features a CUDA extension to the underlying Fortran architecture, is given. Detailed performance benchmarks for thermal plasmas are presented, which demonstrate excellent weak scaling on NERSC's Perlmutter supercomputer and high levels of absolute performance. The robustness of the code to model a variety of physical systems is demonstrated via simulations of Weibel filamentation and laser-wakefield acceleration run with dynamic load balancing. Finally, measurements and analysis of energy consumption are provided that indicate that the GPU algorithm is up to ~14 times faster and ~7 times more energy efficient than the optimized CPU algorithm on a node-to-node basis. The described development addresses the PIC simulation community's computational demands both by contributing a robust and performant GPU-accelerated PIC code and by providing insight into efficient use of GPU hardware.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Modern CFD applications for the design of a reacting shear layer facility

The RPLUS2D code, capable of calculating high speed reacting flows, was adopted to design a compressible shear layer facility. In order to create reacting shear layers at high convective Mach numbers, hot air streams at supersonic speeds, rendered by converging-diverging nozzles, must be provided. A finite rate chemistry model is used to simulate the nozzle flows. Results are compared with one-dimensional solutions at chemical equilibrium. Additionally, a two equation turbulence model with compressibility effects was successfully incorporated with the RPLUS code. The model was applied to simulate a supersonic shear layer. Preliminary results show favorable comparisons with the experimental data.

Yu, S. T.↗

Modern CFD applications for the design of a reacting shear layer facility

The RPLUS2D code, capable of calculating high speed reacting flows, has been adopted to design a compressible shear layer facility. In order to create reacting shear layers at high convective Mach numbers, hot air streams at supersonic speeds, render by converging-diverging nozzles, must be provided. A finite rate chemistry model is used to simulate the nozzle flows. Results are compared with one-dimensional, chemically equilibrium solutions. Additionally, a two equation turbulence model with compressibility effects has been successfully incorporated with the RPLUS code. The model has been applied to simulate a supersonic shear layer. Preliminary results show favorable comparisons with the experimental data.

Yu, S. T.↗

Meanline Analysis of Turbines with Choked Flow in the Object-Oriented Turbomachinery Analysis Code

The prediction of turbomachinery performance characteristics is an important part of the conceptual aircraft engine design process. During this phase, the designer must examine the effects of a large number of turbomachinery design parameters to determine their impact on overall engine performance and weight. The lack of detailed design information available in this phase necessitates the use of simpler meanline and streamline methods to determine the turbomachinery geometry characteristics and provide performance estimates prior to more detailed CFD (Computational Fluid Dynamics) analyses. While a number of analysis codes have been developed for this purpose, most are written in outdated software languages and may be difficult or impossible to apply to new, unconventional designs. The Object-Oriented Turbomachinery Analysis Code (OTAC) is currently being developed at NASA Glenn Research Center to provide a flexible meanline and streamline analysis capability in a modern object-oriented language. During the development and validation of OTAC, a limitation was identified in the code's ability to analyze and converge turbines as the flow approached choking. This paper describes a series of changes which can be made to typical OTAC turbine meanline models to enable the assessment of choked flow up to limit load conditions. Results produced with this revised model setup are provided in the form of turbine performance maps and are compared to published maps.

Choked Flow↗

Computations of Axisymmetric Flows in Hypersonic Shock Tubes

A time-accurate two-dimensional fluid code is used to compute test times in shock tubes operated at supersonic speeds. Unlike previous studies, this investigation resolves the finer temporal details of the shock-tube flow by making use of modern supercomputers and state-of-the-art computational fluid dynamic solution techniques. The code, besides solving the time-dependent fluid equations, also accounts for the finite rate chemistry in the hypersonic environment. The flowfield solutions are used to estimate relevant shock-tube parameters for laminar flow, such as test times, and to predict density and velocity profiles. Boundary-layer parameters such as bar-delta(sub u), bar-delta(sup *), and bar-tau(sub w), and test time parameters such as bar-tau and particle time of flight t(sub f), are computed and compared with those evaluated by using Mirels' correlations. This article then discusses in detail the effects of flow nonuniformities on particle time-of-flight behind the normal shock and, consequently, on the interpretation of shock-tube data. This article concludes that for accurate interpretation of shock-tube data, a detailed analysis of flowfield parameters, using a computer code such as used in this study, must be performed.

Sharma, Surendra P.↗

A Structural Design Approach Tailored for the Rapid Preliminary Design of Microreactor Components

High-temperature microreactors can play a role in developing reliable, portable energy sources for off-grid remote locations, microgrid concepts, and industrial process heat. Portability and passive safety criteria tend to skew microreactor structural component designs toward complex geometries, high thermal stresses, and design bases with large numbers of startup/shutdown cycles. Current design rules, as typified by Section III of the American Society of Mechanical Engineers (ASME) Boiler & Pressure Vessel Code, are less than optimal for these conditions, particularly for preliminary component designs where developers need to rapidly consider a large number of potential component configurations. This paper presents a design method targeted toward rapid, efficient evaluation of preliminary component designs using modern finite element analysis. The new method retains key connections with the ASME Code rules and design data while streamlining the design approach. This paper presents the design method, several verification examples illustrating the similarities and differences between the new method and the current ASME rules, and the application of the new approach to the evaluation of a test article mimicking key features of a heat pipe–cooled microreactor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The effect of curvature induced broken potential vorticity conservation on drift wave turbulences

Abstract The correlation theory of turbulence suppression (Zhang and Mahajan 1993 Phys. Fluids B5 2000) by velocity shear was constructed by invoking the ansatz of potential vorticity conservation (PVC) that holds for relatively simple (slab) models of drift wave turbulence. It is, therefore, surprising that a detailed modern simulation of the H mode pedestal, using the gyrokinetic code GENE (Hatch et al 2018 Plasma Phys. Control. Fusion 60 084003), found ‘striking agreement’ with the predictions of the analytic model. To understand the reasons for this remarkable agreement, an extended theory that contains finite (magnetic) curvature, and which does not conserve potential vorticity, is developed and ‘solved’ by calculating an inhomogeneous Green function reflecting the fact that the new system has a potential vorticity source. It is, then, demonstrated that the effect of the broken PVC is insignificant for the normal operation parameters in tokamaks; the correction due to curvature is at the order of 2 L 0 / R , where L 0 is the scale length of the local gradient and R is the major radius. The excellent agreement between simulation and slab model 1993 theory is therefore not accidental; the latter can be applied with confidence to the tokamak pedestal.

Physics↗

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

We present hls4ml, a free and open-source platform that translates machine learning (ML) models from modern deep learning frameworks into high-level synthesis (HLS) code that can be integrated into full designs for field-programmable gate arrays (FPGAs) or application-specific integrated circuits (ASICs). With its flexible and modular design, hls4ml supports a large number of deep learning frameworks and can target HLS compilers from several vendors, including Vitis HLS, Intel oneAPI and Catapult HLS. Together with a wider eco-system for software-hardware co-design, hls4ml has enabled the acceleration of ML inference in a wide range of commercial and scientific applications where low latency, resource usage, and power consumption are critical. In this paper, we describe the structure and functionality of the hls4ml platform. The overarching design considerations for the generated HLS code are discussed, together with selected performance results.

FOS: Computer and information sciences↗

Ice Accretion Prediction for a Typical Commercial Transport Aircraft

Ice accretion calculations were made for a modern commercial transport using the NASA Lewis LEWICE3D ice accretion code. The ice accretion calculations were made for the wing and horizontal tail using both isolated flow models and flow models incorporating the entire airplane. The isolated flow model calculations were made to assess the validity of using these simplified models in lieu of the entire model in the ice accretion analysis of full aircraft. Ice shapes typifying a rime and a mixed ice shape were generated for a 30 minute hold condition. In general, the calculated ice shapes looked reasonable and appeared representative of a rime and a mixed ice conditions. The isolated flow model simplification was good for the main wing except at the root where it overpredicted the amount of accreted ice relative to the full aircraft flow model. For the horizontal tail the size and amount of predicted ice compared well for the two flow models, but the position of the accretions were more towards the upper surface for the aircraft flow model relative to the isolated flow model. This was attributed to downwash from the main wing which resulted in a lower effective angle of attack for the aircraft tail.

Bidwell, C. S.↗

Ice accretion prediction for a typical commercial transport aircraft

Ice accretion calculations were made for a modern commercial transport using the NASA Lewis LEWICE3D ice accretion code. The ice accretion calculations were made for the wing and horizonal tail using both isolated flow models and flow models incorporating the entire airplane. The isolated flow model calculations were made to assess the validity of using these simplified models in lieu of the entire model in the ice accretion analysis for full aircraft. Ice shapes typifying a rime and a mixed ice shape were generated for a 30 minute hold condition. In general, the calculated ice shapes looked reasonable and appeared representative of a rime and a mixed ice conditions. The isolated flow model simplification was good for the main wing except at the root where it overpredicted the amount of accreted ice relative to the full aircraft flow model. For the horizontal tail the size and amount of predicted ice compared well for the two flow models, but the position of the accretions were more towards the upper surface for the aircraft flow model relative to the isolated flow model. This was attributed to downwash from the main wing which resulted in a lower effective angle of attack for the aircraft tail.

Bidwell, C. S.↗

Uplift of Ionospheric Oxygen Ions During Extreme Magnetic Storms

Research reported earlier in literature was conducted relating to estimation of the ionospheric electrical field, which may have occurred during the September 1859 Carrington geomagnetic storm event, with regard to modern-day consequences. In this research, the NRL SAMI2 ionospheric code has been modified and applied the estimated electric field to the dayside ionosphere. The modeling was done at 15-minute time increments to track the general ionospheric changes. Although it has been known that magnetospheric electric fields get down into the ionosphere, it has been only in the last ten years that scientists have discovered that intense magnetic storm electric fields do also. On the dayside, these dawn-to-dusk directed electric fields lift the plasma (electrons and ions) up to higher altitudes and latitudes. As plasma is removed from lower altitudes, solar UV creates new plasma, so the total plasma in the ionosphere is increased several-fold. Thus, this complex process creates super-dense plasmas at high altitudes (from 700 to 1,000 km and higher).

Tsurutani, Bruce T.↗