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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

PARIS: Predicting application resilience using machine learning

The traditional method to study application resilience to errors in HPC applications uses fault injection (FI), a time-consuming approach. Furthermore, while analytical models have been built to overcome the inefficiencies of FI, they lack accuracy. In this paper, we present PARIS, a machine-learning method to predict application resilience that avoids the time-consuming process of random FI and provides higher prediction accuracy than analytical models. PARIS captures the implicit relationship between application characteristics and application resilience, which is difficult to capture using most analytical models. We overcome many technical challenges for feature construction, extraction, and selection to use machine learning in our prediction approach. Our evaluation on 16 HPC benchmarks shows that PARIS achieves high prediction accuracy. PARIS is up to 450x faster than random FI (49x on average). Compared to the state-of-the-art analytical model, PARIS is at least 63% better in terms of accuracy and has comparable execution time on average.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Fraction of the theoretical specific energy achieved on pack level for hypothetical battery chemistries

In valuing new active materials chemistries for advanced batteries, the theoretical specific energy is commonly used to motivate research and development. A packaging factor is then used to relate the theoretical specific energy to the pack-level specific energy. As this factor is typically assumed constant, higher theoretical specific energies are judged to result in higher pack-level specific energies. Here, to test this implicit assumption, we calculated the fraction of the theoretical specific energy achieved on the pack level for hypothetical cell chemistries with various open-circuit voltages and theoretical specific energies using a peer-review bottom-up battery design model. The pack-level specific energy shows significant dependence on the open-circuit voltage and electrochemical impedance due to changes in the quantity of inactive materials required. At low-valued average open-circuit voltages, systems with dramatically different theoretical specific energies may result in battery packs similar in mass and volume. The fraction of the theoretical specific energy achieved on the pack level is higher for the lower theoretical specific energy systems mainly because the active materials mass dominates the pack mass. Finally, low-valued area-specific impedance is shown to be critical for chemistries of high theoretical specific energy and low open-circuit voltage to achieve higher pack-level specific energies.

25 ENERGY STORAGE↗
DOE OSTI2020

Multiscale model predictive control of battery systems for frequency regulation markets using physics-based models

In this work, we propose a multiscale model predictive control (MPC) framework for stationary battery systems that exploits high-fidelity models to trade-off short-term economic incentives provided by energy and frequency regulation (FR) markets and long-term degradation effects. We find that the MPC framework can drastically reduce long-term degradation while properly responding to FR and energy market signals (compared to MPC formulations that use low-fidelity models). Our results also provide evidence that sophisticated battery models can be embedded within closed-loop MPC simulations by using modern nonlinear programming solvers (we provide an efficient and easy-to-use implementation in Julia). We use insights obtained with our simulations to design a low-complexity MPC formulation that matches the behavior obtained with high-fidelity models. This is done by designing a suitable terminal penalty term that implicitly captures long-term degradation. The results suggest that complex degradation behavior can be accounted for in low-complexity MPC formulations by properly designing the cost function. We believe that our proof-of-concept results can be of industrial relevance, as battery vendors are seeking to participate in fast-changing electricity markets while maintaining asset integrity.

42 ENGINEERING↗
DOE OSTI2021

A constitutive model for glass–ceramic materials

Glass–ceramics have received recent attention for use in glass–ceramic to metal hermetic seals. Due to their heterogeneous microstructure, these materials exhibit a number of advantageous responses over conventional glass based seals. Key amongst them is the possibility of a controllable thermal strain response and apparent coefficient of thermal expansion which may be used to minimize thermally induced residual stresses for aforementioned seals. Furthermore, these behaviors result from an inorganic glass matrix and variety of crystalline ceramic phases including silica polymorph(s) that may undergo reversible solid-to-solid transformations with associated inelastic strain. Correspondingly, these materials exhibit complex thermomechanical responses associated with multiple inelastic mechanisms (viscoelasticity and phase transformation). While modeling these behaviors is essential for developing and analyzing the corresponding applications, no such model exists. Therefore, in this work a three-dimensional continuum constitutive model for glass–ceramic materials combining these various inelastic mechanisms is developed via an internal state variable approach. A corresponding fully implicit three dimensional numerical formulation is also proposed and implemented. The model is used to simulate existing experiments and validate the proposed formalism. As an example, the simple seal problem of a glass–ceramic seal inside a concentric metal shell is explored. Finally, the impact of the cooling rates, viscoelastic shift factors, and inelastic strain on final residual stress state are all investigated and the differing contributions highlighted.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Fragmentation analysis of a bar with the Lip-field approach

The Lip-field approach was introduced in Moës and Chevaugeon (2021) as a new way to regularize softening material models. It was tested in 1D quasistatic in Moës and Chevaugeon (2021) and 2D quasistatic in Chevaugeon and Moës (2021): this paper extends it to 1D dynamics, on the challenging problem of dynamic fragmentation. The Lip-field approach formulates the mechanical problem to be solved as an optimization problem, where the incremental potential to be minimized is the non-regularized one. Spurious localization is prevented by imposing a Lipschitz constraint on the damage field. Here, the displacement and damage field at each time step are obtained by a staggered algorithm, that is the displacement field is computed for a fixed damage field, then the damage field is computed for a fixed displacement field. Indeed, these two problems are convex, which is not the case of the global problem where the displacement and damage fields are sought at the same time. The incremental potential is obtained by equivalence with a cohesive zone model, which makes material parameters calibration simple. A non-regularized local damage equivalent to a cohesive zone model is also proposed. It is used as a reference for the Lip-field approach, without the need to implement displacement jumps. These approaches are applied to the brittle fragmentation of a 1D bar with randomly perturbed material properties to accelerate spatial convergence. Both explicit and implicit dynamic implementations are compared. Favorable comparison to several analytical, numerical and experimental references serves to validate the modeling approach.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A publicly available PyTorch-$\mathrm{ABAQUS}$ $\mathrm{UMAT}$ deep-learning framework for level-set plasticity

Here this paper introduces a publicly available PyTorch-ABAQUS deep-learning framework of a family of plasticity models where the yield surface is implicitly represented by a scalar-valued function. In particular, our focus is to introduce a practical framework that can be deployed for engineering analysis that employs a user-defined material subroutine (UMAT/VUMAT) for ABAQUS, which is written in FORTRAN. To accomplish this task while leveraging the back-propagation learning algorithm to speed up the neural-network training, we introduce an interface code where the weights and biases of the trained neural networks obtained via the PyTorch library can be automatically converted into a generic FORTRAN code that can be a part of the UMAT/VUMAT algorithm. To enable third-party validation, we purposely make all the data sets, source code used to train the neural-network-based constitutive models, and the trained models available in a public repository. Furthermore, the practicality of the workflow is then further tested on a dataset for anisotropic yield function to showcase the extensibility of the proposed framework. A number of representative numerical experiments are used to examine the accuracy, robustness and reproducibility of the results generated by the neural network models.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Sensitivity of polycrystal plasticity to slip system kinematic hardening laws for Al 7075-T6

The prediction of formation and early growth of microstructurally small fatigue cracks requires use of constitutive models that accurately estimate local states of stress, strain, and cyclic plastic strain. However, few research efforts have attempted to systematically consider the sensitivity of overall cyclic stress-strain hysteresis and higher order mean stress relaxation and plastic strain ratcheting responses introduced by the slip system back-stress formulation in crystal plasticity, even for face centered cubic (FCC) crystal systems. This paper explores the performance of two slip system level kinematic hardening models using a finite element crystal plasticity implementation as a User Material Subroutine (UMAT) within ABAQUS, with fully implicit numerical integration. The two kinematic hardening formulations aim to reproduce the cyclic deformation of polycrystalline Al 7075-T6 in terms of both macroscopic cyclic stress-strain hysteresis loop shape, as well as ratcheting and mean stress relaxation under strain- or stress-controlled loading with mean strain or stress, respectively. The first formulation is an Armstrong-Frederick type hardening-dynamic recovery law for evolution of the back stress. This approach is capable of reproducing observed deformation under completely reversed uniaxial loading conditions, but overpredicts the rate of cyclic ratcheting and associated mean stress relaxation. The second formulation corresponds to a multiple back stress Ohno-Wang type hardening law with nonlinear dynamic recovery. The adoption of this back stress evolution law greatly improves the capability to model experimental results for polycrystalline specimens subjected to cycling with mean stress or strain. As a result, the relation of such nonlinear dynamic recovery effects are related to slip system interactions with dislocation substructures.

36 MATERIALS SCIENCE↗
DOE OSTI2016

γ-Ray spectroscopy using a binned likelihood approach

The measurement of a reaction cross section from a pulse height spectrum is a ubiquitous problem in experimental nuclear physics. In γ-ray spectroscopy, this is accomplished frequently by measuring the intensity of full-energy primary transition peaks and correcting the intensities for experimental artifacts, such as detection efficiencies and angular correlations. Implicit in this procedure is the assumption that full-energy peaks do not overlap with any secondary peaks, escape peaks, or environmental back- grounds. However, for complex γ-ray cascades, this is often not the case. Furthermore, this technique is difficult to adapt for coincidence spectroscopy, where intensities depend not only on the detection efficiency, but also the detailed decay scheme. We present a method that incorporates the intensities of the entire spectrum (e.g., primary and secondary transition peaks, escape peaks, Compton continua, etc.) into a statistical model, where the transition intensities and branching ratios can be determined using Bayesian statistical inference. This new method provides an elegant solution to the difficulties associated with analyzing coincidence spectra. Finally, we describe it in detail and examine its efficacy in the analysis of 18 O(p,γ) 19 F and 25 Mg(p,γ) 26 Al resonance data. For the 18 O(p,γ) 19 F reaction, the measured branching ratios improve upon the literature values, with a factor of 3 reduction in the uncertainties.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Trace radioactive impurities in final construction materials for EXO-200

Here, we report results from a systematic measurement campaign conducted to identify low radioactivity materials for the construction of the EXO-200 double beta decay experiment. Partial results from this campaign have already been reported in a 2008 paper by the EXO collaboration. Here we release the remaining data, collected since 2007, to the public. The data reported were obtained using a variety of analytic techniques. The measurement sensitivities are among the best in the field. We concluded the construction of the EXO-200 detector and Phase-I data was taken from 2011 to 2014. The detector’s extremely low background implicitly verifies the measurements and the analysis assumptions made during construction and reported in this paper.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

CTF-R: A novel residual-based thermal hydraulic solver

The traditional scientific process has been revolutionized by the advent of computational modeling, but the nuclear industry generally uses "legacy codes," which were developed early in the evolution of computers. One example of a legacy code, the thermal hydraulic subchannel code CTF, is modernized in this work through the development of a novel residual-based version, CTF-R. Unlike its predecessor, CTF-R is not limited by the strict computational limitations of the early 1980's, and can therefore be designed such that it is inherently flexible and easy to use. A case study is examined to demonstrate how the flexibility of the code can be used to improve simulation results. In this example, the coupling between the solid and liquid fields is examined. Traditionally, this coupling is modeled explicitly, which imposes numerical stability limits on the time step size. These limits are derived and it is shown that they are removed when the coupling is made implicit. Further, the development of CTF-R will enable future improvements in next generation reactor modeling, numerical methods, and coupling to other codes. Through the further development of CTF-R and other residual-based codes, state-of-the-art simulation is possible.

42 ENGINEERING↗
DOE OSTI2015

An improved understanding of the natural resonances of moonpools contained within floating rigid-bodies: Theory and application to oscillating water column devices

The fundamental interactions between waves, a floating rigid-body, and a moonpool that is selectively open to atmosphere or enclosed to purposefully induce pressure fluctuations are investigated. The moonpool hydrodynamic characteristics and the hydrodynamic coupling to the rigid-body are derived implicitly through reciprocity relations on an array of field points. By modeling the free surface of the moonpool in this manner, an explicit hydrodynamic coupling term is included in the equations of motion. This coupling results in the migration of the moonpool's natural resonance frequency from the piston frequency to a new frequency when enclosed in a floating rigid-body. Two geometries that highlight distinct aspects of marine vessels and oscillating water column (OWC) renewable energy devices are analyzed to reveal the coupled natural resonance migration. The power performance of these two OWCs in regular waves is also investigated. The air chamber is enclosed and a three-dimensional, linear, frequency domain performance model that links the rigid-body to the moonpool through a linear resistive control strategy is detailed. Furthermore, an analytic expression for the optimal linear resistive control values in regular waves is presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Petascale solvers for anisotropic PDEs in atmospheric modelling on GPU clusters

Memory bound applications such as solvers for large sparse systems of equations remain a challenge for GPUs. Fast solvers should be based on numerically efficient algorithms and implemented such that global memory access is minimised. To solve systems with trillions ( O ( 10 12 ) ) unknowns the code has to make efficient use of several million individual processor cores on large GPU clusters. We describe the multi-GPU implementation of two algorithmically optimal iterative solvers for anisotropic PDEs which are encountered in (semi-) implicit time stepping procedures in atmospheric modelling. In this application the condition number is large but independent of the grid resolution and both methods are asymptotically optimal, albeit with different absolute performance. In particular, an important constant in the discretisation is the CFL number; only the multigrid solver is robust to changes in this constant. We parallelise the solvers and adapt them to the specific features of GPU architectures, paying particular attention to efficient global memory access. We achieve a performance of up to 0.78 PFLOPs when solving an equation with 0.55 · 10 12 unknowns on 16384 GPUs; this corresponds to about 3% of the theoretical peak performance of the machine and we use more than 40% of the peak memory bandwidth with a Conjugate Gradient (CG) solver. Although the other solver, a geometric multigrid algorithm, has a slightly worse performance in terms of FLOPs per second, overall it is faster as it needs less iterations to converge; the multigrid algorithm can solve a linear PDE with half a trillion unknowns in about one second.

Computer Science↗
DOE OSTI2019

Performance of asynchronous optimized Schwarz with one-sided communication

In asynchronous iterative methods on distributed-memory computers, processes update their local solutions using data from other processes without an implicit or explicit global synchronization that corresponds to advancing the global iteration counter. Here in this work, we test the asynchronous optimized Schwarz domain-decomposition iterative method using various one-sided (remote direct memory access) communication schemes with passive target completion. The results show that when one-sided communication is well-supported, the asynchronous version of optimized Schwarz can outperform the synchronous version even for perfectly balanced partitionings of the problem on a supercomputer with uniform nodes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Optimization of processor allocation for domain decomposed Monte Carlo calculations

Load imbalance plagues domain decomposed Monte Carlo calculations when sources are not uniform. Parallel efficiency for domain decomposed Monte Carlo transport calculations improves through a nonuniform allocation of processors over subdomains. In this work, we optimize the allocation with runtime diagnostics collected during a calibration step, then complete the full calculation. The diagnostic-based approach is compared to implicit filtering, an optimization algorithm for bound constrained noisy optimization problems. Finally, we consider both forward and hybrid radiation transport calculations to measure performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Sequentially coupled flow and geomechanical simulation with a discrete fracture model for analyzing fracturing fluid recovery and distribution in fractured ultra-low permeability gas reservoirs

More accurate characterization and prediction of the in-situ distribution of fracturing fluid in fractured reservoirs are needed for enhancing well productivity. In this study, an implicit-sequentially coupled flow/geomechanics simulator incorporating an efficient discrete fracture model is developed to model fluid distribution and recovery performance of ultra-low permeability gas reservoirs. The finite-volume and finite-element methods are used for space discretization of the flow and geomechanics equations, respectively, while the backward Euler method is employed for time discretization. The flow and geomechanics equations are solved sequentially based on fixed-stress splitting. An efficient discrete-fracture model is used to explicitly model the fractured system. Flexible unstructured gridding is employed to model arbitrarily-oriented fractures. The interrelations among pore volume, permeability and geomechanical conditions are considered dynamically using two-way coupled flow and geomechanics computations. The geometry of fracture (networks) due to hydraulic fracturing has significant impacts on the fracturing fluid recovery efficiency and ensuing fluid distribution. Under the same injection volume, the fracturing fluid recovery is higher when the fracture geometry is planar. Fluid recovery is relatively lower whenever natural fractures are activated during fracturing treatments; flowback time is also shortened when complex fracture network with enlarged fracture interface is present. Fracturing fluid in hydraulic fractures may leak off into the natural fractures and subsequently imbibes into the surrounding matrix due to capillarity effects. The fracturing fluid recovery and in-situ fluid distribution are sensitive to the shut-in duration and fracture closure behavior. This study analyzes the coupled flow-geomechanical responses of fractured gas reservoirs during the post-fracturing periods. Understanding the fate of the fracturing fluid can provide insights on, to some extent, the stimulated fracture volume, size of the water invasion zone, and efficiency of the fracturing design. The simulation predictions can also provide more accurate initial reservoir conditions (e.g. distributions of different phases and pressure) for long-term well performance estimation.

42 ENGINEERING↗
DOE OSTI2018

The microscopic model of BiFeO 3

Many years and great effort have been spent constructing the microscopic model for the room temperature multiferroic BiFeO 3 . However, earlier models implicitly assumed that the cycloidal wavevector q was confined to one of the three-fold symmetric axes in the hexagonal plane normal to the electric polarization. Because recent measurements indicate that q can be rotated by a magnetic field, it is essential to properly treat the anisotropy that confines q at low fields. Here, we propose that the anisotropy energy $–K_3S^6$ sin$^6θ$ cos $6ϕ$ confines the wavevectors q to the three-fold axis $ϕ=0$ and $±2π/3$ within the hexagonal plane with $θ=π/2$.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗