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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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At least 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Investigation of HgCdTe waveguide structures with quantum wells for long-wavelength stimulated emission

The photoluminescence and stimulated emission during interband transitions in quantum wells based on HgCdTe placed in an insulator waveguide based on a wide-gap CdHgTe alloy are studied. Heterostructures with quantum wells based on HgCdTe are of interest for the development of long-wavelength lasers in the range of 25–60 μm, which is currently unattainable for quantum-cascade lasers. Optimal designs of quantum wells for attainment of long-wavelength stimulated emission under optical pumping are discussed. It is shown that narrow quantum wells from pure HgTe appear to be more promising for long-wavelength lasers in comparison with wide (potential) wells from the alloy due to the suppression of Auger recombination. It is demonstrated that molecular-beam epitaxy makes it possible to obtain structures for the localization of radiation with a wavelength of up to 25 μm at a high growth rate. Stimulated emission is obtained for wavelengths of 14–6 μm with a threshold pump intensity in the range of 100–500 W/cm{sup 2} at 20 K.

36 MATERIALS SCIENCE↗
DOE OSTI2018

On the Spatial Localization of Free Electrons in 4H-SiC MOSFETS with an n Channel

The problem of the spatial localization of free electrons in 4H-SiC metal—oxide—semiconductor field effect transistors (MOSFETS) with an accumulation- and inversion-type n channel is theoretically analyzed. The analysis demonstrates that, in optimally designed accumulation transistors (ACCUFETs), the average distance from the surface, at which free electrons are localized, may be an order of magnitude larger than that in inversion MOSFETs. This can make 4H-SiC ACCUFETs advantageous as regards the effective carrier mobility in a conducting channel.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Analyzing the suitability of contemporary 3D-stacked PIM architectures for HPC scientific applications

Scaling off-chip bandwidth is challenging due to fundamental limitations, such as a fixed pin count and plateauing signaling rates. Recently, vendors have turned to 2.5D and 3D stacking to closely integrate system components. Interestingly, these technologies can integrate a logic layer under multiple memory dies, enabling computing capability inside a memory stack. This trend in stacking is making PIM architectures commercially viable. In this work, we investigate the suitability of offloading kernels in scientific applications onto 3D stacked PIM architectures. We evaluate several hardware constraints resulted from the stacked structure. We perform extensive simulation experiments and in-depth analysis to quantify the impact of application locality in TLBs, data caches, and memory stacks. Our results also identify design optimization areas in software and hardware for HPC scientific applications.

Peng, Ivy Bo↗
DOE OSTI2021

Gleipnir: toward practical error analysis for Quantum programs

Practical error analysis is essential for the design, optimization, and evaluation of Noisy Intermediate-Scale Quantum(NISQ) computing. However, bounding errors in quantum programs is a grand challenge, because the effects of quantum errors depend on exponentially large quantum states. In this work, we present Gleipnir, a novel methodology toward practically computing verified error bounds in quantum programs. Gleipnir introduces the (ρ,δ)-diamond norm, an error metric constrained by a quantum predicate consisting of the approximate state ρ and its distance δ to the ideal state ρ. This predicate (ρ,δ) can be computed adaptively using tensor networks based on the Matrix Product States. Gleipnir features a lightweight logic for reasoning about error bounds in noisy quantum programs, based on the (ρ,δ)-diamond norm metric. Furthermore, our experimental results show that Gleipnir is able to efficiently generate tight error bounds for real-world quantum programs with 10 to 100 qubits, and can be used to evaluate the error mitigation performance of quantum compiler transformations.

Tao, Runzhou↗
DOE OSTI2019

Materials for Automotive Lightweighting

Reducing the weight of automobiles is a major contributor to increased fuel economy. The baseline materials for vehicle construction, low-carbon steel and cast iron, are being replaced by materials with higher specific strength and stiffness: advanced high-strength steels, aluminum, magnesium, and polymer composites. We find that the key challenge is to reduce the cost of manufacturing structures with these new materials. Maximizing the weight reduction requires optimized designs utilizing multimaterials in various forms. This use of mixed materials presents additional challenges in joining and preventing galvanic corrosion.

36 MATERIALS SCIENCE↗
DOE OSTI2020

In Situ Reliability Investigation of All-Vanadium Redox Flow Batteries by a Stable Reference Electrode

Redox flow batteries (RFBs) have been studied over the past several decades as a promising candidate for stationary energy storage applications. It is therefore important to understand the reliability of RFBs and the mechanisms that cause degradation with time. Contributions from individual electrodes (cathode or anode) are difficult to separate especially for long-term cycle testing, due to the lack of a stable reference electrode. In our work, the reliability and degradation mechanisms of an all-vanadium RFB were investigated by a stable reference electrode based on the dynamic hydrogen electrode (DHE). With factor exploration and design optimization, the newly developed DHE reference electrode demonstrated high accuracy and long-term stability that enables in-situ monitoring of individual electrode signals (potentials and impedances) over hundreds of cycles in a vanadium RFB. This approach enables the full cell degradation to be separated and the degradation attributed to contributions from the cathode and anode. The cathode and anode were found to play quite different roles in the increase in overpotential of the vanadium RFB during long-term cycling. The anode reaction limited both the charge and discharge capacity over 100 cycles. In addition, the negative side also appeared to be the rate limiting factor throughout cycling as determined by EIS measurement. The cathode contributed to the performance degradation as cycling exceeded 50 cycles.

Huang, Qian↗
DOE OSTI2021

Quantifying Uncertainty in Tortuosity Estimates for Porous Electrodes

Measuring tortuosity in porous electrodes is important for understanding rate capability and optimizing design. Here, we describe an approach to determine electrode tortuosities and quantify the associated uncertainties by fitting a P2D model to discharge profiles from a standard rate capability test. A dimensionless current is identified as a design-of-experiment parameter that can be used to identify experiments that return confident estimates of tortuosity, even when other model parameters are not known with certainty. This approach is applied to analysis of L i x V 3 O 8 (LVO) electrodes and L i x N i 0.33 M n 0.33 C o 0.33 O 2 (NMC) electrodes. The details of the assumptions made in these measurements and their impact on the reported uncertainties are discussed. We also perform an uncertainty analysis on the standard method for quantifying tortuosity in the literature: electrochemical impedance spectroscopy collected under blocking electrolyte conditions. We find that confident estimates can be obtained using this approach even when uncertainties in equivalent circuit model parameters are considered.

25 ENERGY STORAGE↗
DOE OSTI2025

Physics-Based Analysis of Cell Imbalances and Aging in Lithium-Ion Battery Modules and Packs

Lithium-ion battery (LIB) packs are a key solution for grid-scale energy storage, enabling grid resilience and supporting critical infrastructure. LIB modules and packs experience current imbalances and uneven cell aging due to various design and operational factors, and require a battery management system (BMS) to continuously monitor and control. In this context, a physics-based modeling framework for LIB modules and packs (liionpack) was enhanced to identify design and control strategies that minimize current imbalance and improve module/pack operation. Simulations of an 8-cell parallel-connected module demonstrate that reducing current imbalance leads to more uniform cell aging and improved module/pack-level degradation predictions. The analysis shows that current imbalance are affected by the electrical resistances. Terminal location significantly affects imbalance, with opposite-end terminal connections at intermediate branches minimizing the imbalance, and the pack circuit construction influences the accuracy of physics-based analysis at the pack scale. This framework enables design optimization of modules and packs through a fast and easy evaluation of pack performance and aging, and supports the development of aging-informed balancing strategies compatible with BMS implementation. Thereby, offering practical pathways to improve reliability and cycle life predictions in large-scale battery energy storage systems.

Ayalasomayajula, Surya Mitra [Oak Ridge National L↗
DOE OSTI2014

Rapid Optimization Library

ROL provides interfaces to and implementations of algorithms for gradient-based unconstrained and constrained optimization. ROL can be used to optimize the response of any client simulation code that evaluates scalar-valued response functions. If the client code can provide gradient information for the response function, ROL will take advantage of it, resulting in faster runtimes. ROL's interfaces are matrix-free, in other words ROL only uses evaluations of scalar-valued and vector-valued functions. ROL can be used to solve optimal design problems and inverse problems based on a variety of simulation software.

Kouri, DrewKouri↗
DOE OSTI2018

Paracousti v. 2.0.0

Paracousti simulates 3-D acoustic wave propagation in fixed (non-moving) complex media. It solves the linear acoustic equations of motion using the velocity-pressure system of first order linear differential equations on a finite-difference Cartesian grid using Newton’s law of motion and mass continuity equations. It also has the ability to incorporate acoustic attenuation to simulate non-recoverable energy losses via the velocity-memory-pressure system of linear differential equations. We assume stationary, non-heat conducting, adiabatic media (fluid) where the background sound speed and material density are fixed in time. Capabilities include massively parallel design, optimization for high contrast media interfaces, inclusion of arbitrary pressure and force sources defined by the user, inclusion of arbitrary pressure and velocity receivers defined by the user, acoustic wavefield snapshots in time for visualization, and convolutional perfectly matched layers to minimize artificial grid boundary reflections. Paracousti was built upon the foundational framework of TDAAPS (Time-Domain Atmospheric Acoustic Propagation Suite) by Neill Symons, Dave Aldridge, and Leiph Preston.

Preston, Leiph↗
DOE OSTI2019

Hybrid Optimization and Performance Platform (HOPP)

As part of NREL's Hybrid Energy Systems Research, this software assesses optimal designs for the deployment of utility-scale hybrid energy plants, particularly considering wind, solar and storage.

Tripp, CharlesEdison [National Renewable Energy La↗
DOE OSTI2021

Deeper Fluids

A framework for building and training neural network surrogates for CFD simulation, with a focus on quickly simulating volume fraction dynamics for carbon capture efficiency prediction. Augments the Deep Fluids (Kim et al., 2019) approach as described in our paper "Latent Space Simulation for Carbon Capture Design Optimization" (Bartoldson et al., 2021).

Nguyen, PhuocChanh N↗
DOE OSTI2022

Latent Space Dynamics Identification

LaSDI is a data-driven physical simulation software that forms a latent space for a given high-fidelity model and discovers a set of ordinary differential equations for the latent space dynamics. It allows a fast and accurate solution process, which is useful for multi-query decision making applications, such as design optimization and uncertainty quantification. The performance of the LaSDI framework is demonstrated on four different problems, i.e., 1D and 2D Burgers equations, nonlinear heat conduction, and radial advection problems. Both linear and nonlinear compression techniques, such as neural network and proper orthogonal decomposition, are used to form a latent space. A concept of local dynamics identification procedure is introduced to enable a parametric model, which enhances the accuracy level over a given parameter space.

Fries, William↗
DOE OSTI2023

JuliaOceanWaves

SAND2023-05107O JuliaOceanWaves is a collection of packages and functions for modeling wave energy converters. The open-source software is designed to be used by the wave energy community to model new concepts, perform design optimization, and more. Capabilities include: • A representation of ocean wave spectra and input/output (e.g. read from National Oceanic and Atmospheric Administration buoys) and post-processing functionalities; • A solver for the linear potential flow radiation and diffraction equations for wave forcing on floating structures. • Solving the floating body linear dynamics in the frequency domain. Future additions to the software will include solving non-linear floating body dynamics in the time-domain through time-marching Ordinary Differential Equation solvers and the pseudo-spectral optimization method. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Michelen Strofer, Carlos↗
DOE OSTI2023

PINNSTRIPES (Physics-Informed Neural Network SurrogaTe for Rapidly Identifying Parameters in Energy Systems) [SWR-22-12]

Energy systems models typically take the form of complex partial differential equations which make multiple forward calculations prohibitively expensive. Fast and data-efficient construction of surrogate models is of utmost importance for applications that require parameter exploration such as design optimization and Bayesian calibration. In presence of a large number of parameters, surrogate models that capture correct dependencies may be difficult to construct with traditional techniques. The issue is addressed here with the formulation of the surrogate model constructed via Physics-Informed Neural Networks (PINN) which capture the dependence with respect to the parameters to estimate, while using a limited amount of data. Since forward evaluations of the surrogate model are cheap, parameter exploration is made inexpensive, even when considering a large number of parameters.

Hassanaly, Malik↗
DOE OSTI2016

Identification of Inhibitors of the Association of ZAP-70 with the T Cell Receptor by High-Throughput Screen

ZAP-70 is a critical molecule in the transduction of T cell antigen receptor signaling and the activation of T cells. Upon activation of the T cell antigen receptor, ZAP-70 is recruited to the intracellular ζ-chains of the T cell receptor, where ZAP-70 is activated and colocalized with its substrates. Inhibitors of ZAP-70 could potentially function as treatments for autoimmune diseases or organ transplantation. In this work, we present the design, optimization, and implementation of a screen for inhibitors that would disrupt the interaction between ZAP-70 and the T cell antigen receptor. Finally, the screen is based on a fluorescence polarization assay for peptide binding to ZAP-70.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Priority research directions for in situ data management: Enabling scientific discovery from diverse data sources

In January 2019, the US Department of Energy, Office of Science program in Advanced Scientific Computing Research, convened a workshop to identify priority research directions (PRDs) for in situ data management (ISDM). A fundamental finding of this workshop is that the methodologies used to manage data among a variety of tasks in situ can be used to facilitate scientific discovery from many different data sources—simulation, experiment, and sensors, for example—and that being able to do so at numerous computing scales will benefit real-time decision-making, design optimization, and data-driven scientific discovery. This article describes six PRDs identified by the workshop, which highlight the components and capabilities needed for ISDM to be successful for a wide variety of applications—making ISDM capabilities more pervasive, controllable, composable, and transparent, with a focus on greater coordination with the software stack and a diversity of fundamentally new data algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Spray characterization for engine combustion network Spray G injector using high-fidelity simulation with detailed injector geometry

This article presents a computational fluid dynamics study of the engine combustion network Spray G, focusing on the transient characteristics of the spray during the start of injection and the impacts of nozzle geometry details derived from the manufacturing process. The large-eddy-simulation method, coupled with the volume-of-fluid method, was used to model the high-speed turbulent two-phase flow. A moving-needle boundary condition was applied to capture the internal flow boundary condition accurately. The injector geometry was measured with micron-level resolution using X-ray tomographic imaging at the Advanced Photon Source at Argonne National Laboratory, providing detailed machining tolerance and defects from manufacturing and a realistic rough surface. For comparison, a nominal geometry and a modified geometry incorporating measured large-scale geometric features but no surface details were also used in the simulations. Spray characteristics such as mass flow rate, injection velocity, and Sauter mean diameter were analyzed. Significantly distinct spray characteristics in terms of injection velocity, spray morphology, and primary breakup mechanism were predicted using different nozzle geometries, which is mainly attributable to the realistic surface finish and manufacturing defects. The measured high-resolution geometry predicts a lower injection velocity, a wider-spreading spray, and an overall slower breakup rate with evident injector tip wetting compared to the ideally smooth nozzle boundary. This result implies that the manufacturing details of the injector, which are usually ignored in fuel injection studies, have a significant impact on the spray development process and should be taken into account for design optimization.

Yue, Zongyu↗