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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Multiscale Electricity Modeling for Evaluating Carbon Capture and Sequestration Technologies (MEME-CCS)

This effort employs and adapts an existing, rigorous multiscale electricity modeling platform at the National Renewable Energy Laboratory (NREL) to evaluate carbon capture and sequestration (CCS) and negative emissions technologies (NET) from the ARPA-E FLECCS program. NREL's modeling platform includes the Regional Energy Deployment System (ReEDS) electric sector capacity expansion model, which projects future electricity generation mixes at sub-state-level resolution that are downscaled to the unit-level to enable hourly, zonal or nodal electricity production cost modeling in the PLEXOS model. The resulting hourly price data from PLEXOS is provided to technology developers under the ARPA-E FLECCS program to enable technology-specific economic analysis. The ReEDS-PLEXOS modeling suite is well-established for examining electric sector futures with high renewable energy penetrations, energy storage, electrification, and distributed generation. The key advancement proposed herein utilizes collaboration with CCS experts at the University of Wyoming and the FLECCS teams to create innovative methods for representing CCS and NET in the ReEDS and PLEXOS models. Expanded technology options, new operational parameterizations, and detailed data defining CO2 capture, transportation, and storage systems are being integrated into these models to allow an unprecedented combination of scope and resolution for exploring the future of CCS and NET. The resulting capabilities will take advantage of high-performance computing resources to permit wide-ranging scenario analysis to assess CCS and NET deployment under alternative CO2 prices, fossil fuel prices, electricity demand growth, and other electric sector characteristics. Final outcomes will include publicly available hourly grid operation and price data for any U.S. region of interest along with open-access capacity expansion tools for evaluating CCS/NET systems. These products will help an emerging CCS/NET industry in the United States by providing economics-driven guidance to technology developers while informing policy and investment decisions in the public and private sectors.

air capture↗
NASA NTRS1985

Flight test experience and controlled impact of a large, four-engine, remotely piloted airplane

A controlled impact demonstration (CID) program using a large, four engine, remotely piloted transport airplane was conducted. Closed loop primary flight control was performed from a ground based cockpit and digital computer in conjunction with an up/down telemetry link. Uplink commands were received aboard the airplane and transferred through uplink interface systems to a highly modified Bendix PB-20D autopilot. Both proportional and discrete commands were generated by the ground pilot. Prior to flight tests, extensive simulation was conducted during the development of ground based digital control laws. The control laws included primary control, secondary control, and racetrack and final approach guidance. Extensive ground checks were performed on all remotely piloted systems. However, manned flight tests were the primary method of verification and validation of control law concepts developed from simulation. The design, development, and flight testing of control laws and the systems required to accomplish the remotely piloted mission are discussed.

Kempel, R. W.↗
NASA NTRS1985

Flight test experience and controlled impact of a large, four-engine remotely piloted airplane

A controlled impact demonstration (CID) program using a large, four engine, remotely piloted transport airplane was conducted. Closed loop primary flight control was performed from a ground based cockpit and digital computer in conjunction with an up/down telemetry link. Uplink commands were received aboard the airplane and transferred through uplink interface systems to a highly modified Bendix PB-20D autopilot. Both proportional and discrete commands were generated by the ground pilot. Prior to flight tests, extensive simulation was conducted during the development of ground based digital control laws. The control laws included primary control, secondary control, and racetrack and final approach guidance. Extensive ground checks were performed on all remotely piloted systems. However, manned flight tests were the primary method of verification and validation of control law concepts developed from simulation. The design development, and flight testing of control laws and the systems required to accomplish the remotely piloted mission are discussed.

Kempel, R. W.↗
DOE OSTI2019

Quantum simulations of excited states with active-space downfolded Hamiltonians

Many-body techniques based on the double unitary coupled cluster ansatz (DUCC) can be used to downfold electronic Hamiltonians into low-dimensional active spaces. It can be shown that the resulting dimensionality reduced Hamiltonians are amenable for quantum computing. Recent studies performed for several benchmark systems using quantum phase estimation (QPE) algorithms demonstrated that these formulations can recover a significant portion of ground-state dynamical correlation effects that stem from the electron excitations outside of the active space. These results have also been confirmed in studies of ground-state potential energy surfaces using quantum simulators. In this letter, we study the effectiveness of the DUCC formalism in describing excited states. We also emphasize the role of the QPE formalism and its stochastic nature in discovering/identifying excited states or excited-state processes in situations when the knowledge about the true configurational structure of a sought after excited state is limited or postulated (due to the specific physics driving excited-state processes of interest). In this context, we can view the QPE algorithm as an engine for verifying various hypotheses for excited-state processes and providing statistically meaningful results that correspond to the electronic state(s) with the largest overlap with a postulated configurational structure. We illustrate these ideas on examples of strongly cor- related molecular systems, characterized by small energy gaps and high density of quasi-degenerate states around the Fermi level.

quantum chemistry, quantum computing, computationa↗
DOE OSTI2023

Comparison of spontaneous emission in trapped-ion multiqubit gates at high magnetic fields

Penning traps have been used for performing quantum simulations and sensing with hundreds of ions and provide a promising route toward scaling up trapped ion quantum platforms because of the ability to trap and control hundreds or thousands of ions in two- and three-dimensional crystals. In both Penning traps and the more common RF Paul traps, lasers are often used to drive multi-qubit entangling operations. A leading source of decoherence in these operations is off resonant spontaneous emission. While many trapped ion quantum computers or simulators utilize clock qubits, other systems, especially those with high magnetic fields such as Penning traps, rely on Zeeman qubits, which require a more complex calculation of this decoherence. We therefore examine theoretically the impacts of spontaneous emission on quantum gates performed with trapped-ion ground state Zeeman qubits in a high magnetic field. In particular, we consider two types of gates—light-shift ($\hat{σ}^z_i$ $\hat{σ}^z_j$) gates and Mølmer-Sørensen ($\hat{σ}^x_i$ $\hat{σ}^x_j$) gates—obtained with laser beams directed approximately perpendicular to the magnetic field (the quantization axis) and compare the decoherence errors in each. Within each gate type, we also compare different operating points with regards to the detunings, polarizations, and required intensity of the laser beams used to drive the gates. Here, we show that both gates can have similar performance at their optimal operating conditions at high magnetic fields and examine the experimental feasibility of various operating points. By examining the magnetic field dependence of each gate, we demonstrate that, when the P state fine structure splitting is large compared to the Zeeman splittings, the theoretical performance of the Mølmer-Sørensen gate is significantly better than that of the light-shift gate. Additionally, for the light-shift gate, we make an approximate comparison between the fidelities that can be achieved at high fields with the fidelities of state-of-the-art two-qubit trapped ion quantum gates. We show that, with regards to spontaneous emission, the achievable fidelity of the current NIST configuration is about an order of magnitude below that of the best low-field gates, but we also discuss several alternative configurations with potential error rates that are comparable with those for state-of-the art trapped ion gates.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2006

A Preliminary Foil Gas Bearing Performance Map

Recent breakthrough improvements in foil gas bearing load capacity, high temperature tribological coatings and computer based modeling have enabled the development of increasingly larger and more advanced Oil-Free Turbomachinery systems. Successful integration of foil gas bearings into turbomachinery requires a step wise approach that includes conceptual design and feasibility studies, bearing testing, and rotor testing prior to full scale system level demonstrations. Unfortunately, the current level of understanding of foil gas bearings and especially their tribological behavior is often insufficient to avoid developmental problems thereby hampering commercialization of new applications. In this paper, a new approach loosely based upon accepted hydrodynamic theory, is developed which results in a "Foil Gas Bearing Performance Map" to guide the integration process. This performance map, which resembles a Stribeck curve for bearing friction, is useful in describing bearing operating regimes, performance safety margins, the effects of load on performance and limiting factors for foil gas bearings.

DellaCorte, Christopher↗
NASA NTRS2019

A common platform for DSN receiver development

NASA's Deep Space Network is currently updating a number of sub systems within the Signal Processing Centers at its Deep Space Communication Complexes in order to modernize aging equipment in the downlink receivers for telemetry, tracking, radio science, and radio astronomy. To reduce development costs and increase commonality among these traditionally custom-built receivers, the implementation team has developed a flexible architecture built primarily around commercial off-the-shelf hardware compliant with the Micro Telecommunications Computing Architecture (uTCA) specification and commercial high speed 10Gbit Ethernet switches. Custom firmware and software are being developed to perform the required signal processing functions needed to replace the legacy systems in a phased implementation approach which establishes a new digital Intermediate Frequency (IF) signal distribution system first, followed by implementations of various receiver functions as dictated by need. The first of these new receivers, the Open Loop Receiver, will come online in the Fall of 2018. A description of the new architecture, referred to as the “Common Platform”, will be provided followed by an overview of the phased implementation approach and initial OLR performance results.

Navarro, Robert↗
DOE OSTI2016

A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers

Current Deep Learning models use highly optimized convolutional neural networks (CNN) trained on large graphical processing units (GPU)-based computers with a fairly simple layered network topology, i.e., highly connected layers, without intra-layer connections. Complex topologies have been proposed, but are intractable to train on current systems. Building the topologies of the deep learning network requires hand tuning, and implementing the network in hardware is expensive in both cost and power.In this paper, we evaluate deep learning models using three different computing architectures to address these problems: quantum computing to train complex topologies, high performance computing (HPC) to automatically determine network topology, and neuromorphic computing for a low-power hardware implementation. Due to input size limitations of current quantum computers we use the MNIST dataset for our evaluation.The results show the possibility of using the three architectures in tandem to explore complex deep learning networks that are untrainable using a von Neumann architecture. We show that a quantum computer can find high quality values of intra-layer connections and weights, while yielding a tractable time result as the complexity of the network increases; a high performance computer can find optimal layer-based topologies; and a neuromorphic computer can represent the complex topology and weights derived from the other architectures in low power memristive hardware.This represents a new capability that is not feasible with current von Neumann architecture. It potentially enables the ability to solve very complicated problems unsolvable with current computing technologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Autonomy Loops for Monitoring, Operational Data Analytics, Feedback, and Response in HPC Operations

Many High Performance Computing (HPC) facilities have developed and deployed frameworks in support of continuous monitoring and operational data analytics (MODA) to help improve efficiency and throughput. Because of the complexity and scale of systems and workflows and the need for low-latency response to address dynamic circumstances, automated feedback and response have the potential to be more effective than current human-in-the-loop approaches which are laborious and error prone. Progress has been limited, however, by factors such as the lack of infrastructure and feedback hooks, and successful deployment is often site- and case-specific. In this position paper we report on the outcomes and plans from a recent Dagstuhl Seminar, seeking to carve a path for community progress in the development of autonomous feedback loops for MODA, based on the established formalism of similar (MAPE-K) loops in autonomous computing and self-adaptive systems. By defining and developing such loops for significant cases experienced across HPC sites, we seek to extract commonalities and develop conventions that will facilitate interoperability and interchangeability with system hardware, software, and applications across different sites, and will motivate vendors and others to provide telemetry interfaces and feedback hooks to enable community development and pervasive deployment of MODA autonomy loops.

autonomy loops↗
DOE OSTI2019

DCA++: A software framework to solve correlated electron problems with modern quantum cluster methods

We present the first open release of the DCA++ project, a high-performance research software framework to solve quantum many-body problems with cutting edge quantum cluster algorithms. DCA++ implements the dynamical cluster approximation (DCA) and its DCA extension with a continuous self-energy. The algorithms capture nonlocal correlations in strongly correlated electron systems, thereby giving insight into high-$T_c$ superconductivity. The code’s scalability allows efficient usage of systems at all scales, from workstations to leadership computers. With regard to the increasing heterogeneity of modern computing machines, DCA++ provides portable performance on conventional and emerging new architectures, such as hybrid CPU–GPU, sustaining multiple petaflops on ORNL’s Titan and CSCS’ Piz Daint supercomputers. Moreover, we show how sustainable and scalable development of the code base has been achieved by adopting standard techniques of the software industry. These include employing a distributed version control system, applying test-driven development and following continuous integration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Multi-Scale Modeling of Thermal-Fluid Phenomena Related to Loss of Forced Circulation Transient in HTGRs

Under the support of DOE-NE’s Nuclear Energy Advanced Modeling and Simulation (NEAMS), an effort had been pursued to support High Temperature Gas-cooled Reactors (HTGR) technology development and its modeling and simulation needs. There was a particular need for advanced modeling & simulation tools to predict thermal-fluid behavior in the nuclear reactor primary system, especially the core and lower and upper plena, during safety-related transients. In this report, two main such activities were presented: 1) system level HTGR simulations using system analysis code SAM for both normal operating and accident conditions; and 2) three-dimensional (3D) computational fluid dynamics (CFD) simulations on Deteriorated Turbulent Heat Transfer (DTHT) of interest to HTGR transients, including code benchmark and closure correlation development. In this work, Modular High Temperature Gas-cooled Reactor (MHTGR) full loop simulations were performed using System Analysis Module (SAM) code. Two approaches were used to model the reactor core; (i) unit-cell or lumped parameter model, and (ii) detailed ring model, to address the different needs under different reactor conditions. Aside from the core model changes other reactor components in the primary system, such as upper/lower plenum, heat exchanger and blower etc, were kept the same. In the unit-cell core model, the lumped parameter approach was used to model the coolant channels and the heat structures using 1-D and 2-D components, respectively. The fuel assembly heat structure was modeled based on unit-cell thickness approximation. In normal and controlled operating conditions, the calculated maximum temperatures for both coolant and heat structures were within the designed limits. The unit-cell model is, however, not able to capture the radial heat conduction through fuel assemblies, which is the dominant heat transfer mechanism during accident transients, such as pressurized conduction cooldown (PCC) event. To address this modeling challenge, ring models were developed. A simplified ring model was developed first. In this simplified model, the active core was simulated with 9 circular rings consists of 6 rings for homogenized fuel heat structure and 3 rings for gas coolant. It was quickly found that this model gives rather large simulation error as it was not able to correctly capture the solid structure representative geometries. A detailed ring model was developed to address this issue. The active core was simulated with 99 circular rings consists of 66 rings for homogenized fuel heat structure and 33 rings for gas coolant. In both ring models, six additional rings were included to represent inner reflector, outer reflector, core barrel, Reactor Pressure Vessel (RPV), RPV coolant channel, and Reactive Cavity Cooling System (RCCS). The detailed ring model was applied in two different SAM simulations; (i) normal operating conditions, and (ii) accident scenarios (more specifically, PCC event), for MHTGR design. In both simulations, the SAM calculated results for coolant and heat structure temperatures were within the reactor designed limits. The newly proposed detailed ring model approach in this work has proved to be a promising method to address the challenging modeling and simulation needs in the MHTGR design. As demonstrated in this work, this model was suitable for MHTGR simulations under both normal and accident conditions. Apart from the SAM model development for gas-cooled reactors, 3D Computational Fluid Dynamics (CFD) models were developed and validated with relaminarized Deteriorated Turbulent Heat Transfer (DTHT) MIT benchmark test. Two different CFD codes, Nek5000 and STAR-CCM+, were used for this benchmark activity. Compared with MIT data, Nek5000 shows very good agreement between its simulated and experimentally measured wall temperatures. In contrast, STAR-CCM+ under-predicted wall temperature due to over predicted turbulence in the wall region. The Nek5000 code was also used to develop wall-heat transfer correlations for laminar flow in cylindrical tube. Several simulations were performed for various Reynolds flow and wall heat fluxes. Significant deviations were found when compared the predicted heat transfer coefficient and the Sieder-Tate correlation. A new set of heat transfer correlation was proposed for laminar flow which is valid for 400<Re<2000.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Simulation and Experimental Study of Metal Organic Frameworks Used in Adsorption Cooling

Metal-organic frameworks (MOFs) have recently attracted enormous interest over the past few years in energy storage and gas separation, yet there have been few reports for adsorption cooling applications. Adsorption cooling technology is an established alternative to mechanical vapor compression refrigeration systems and is an excellent alternative in industrial environments where waste heat is available. We explored the use of MOFs that have very high mass loading and relatively low heats of adsorption, with certain combinations of refrigerants to demonstrate a new type of highly efficient adsorption chiller. Computational fluid dynamics combined with a system level lumped-parameter model have been used to project size and performance for chillers with a cooling capacity ranging from a few kW to several thousand kW. These systems rely on stacked micro/mini-scale architectures to enhance heat and mass transfer. Recent computational studies of an adsorption chiller based on MOFs suggests that a thermally-driven coefficient of performance greater than one may be possible, which would represent a fundamental breakthrough in performance of adsorption chiller technology. Presented herein are computational and experimental results for hydrophyilic and fluorophilic MOFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Ecosystems for Scientific Computing in the Age of AI

Scientific computing is at an inflection point. Artificial intelligence (AI) is reshaping how scientific software is developed, how teams collaborate, how projects are governed, and how the next generation is trained. Drawing on insights from a 2025 workshop report, this article argues that the future of discovery will depend on agile, robust ecosystems built through socio-technical co-design—the intentional integration of technical and human systems. This perspective is essential for ensuring that future scientific computing remains trustworthy, sustainable, and scalable. It combines advances in AI, high-performance computing, and software with new models for cross-disciplinary collaboration, education, and workforce development. Key recommendations include building modular, trustworthy AI-enabled software ecosystems; enabling teams to integrate AI into scientific workflows while preserving human creativity, integrity, and rigor; and developing adaptive training pathways that keep pace with rapid technological change. By sharing these perspectives, we hope to stimulate broader community dialogue and encourage coordinated action.

AI↗
DOE OSTI2023

Qompress: Efficient Compilation for Ququarts Exploiting Partial and Mixed Radix Operations for Communication Reduction

Quantum computing is in an era of limited resources. Current hardware lacks high fidelity gates, long coherence times, and the number of computational units required to perform meaningful computation. Contemporary quantum devices typically use a binary system, where each qubit exists in a superposition of the 0 and 1 states. Furthermore, it is often possible to access the 2 or even 3 states in the same physical unit by manipulating the system in different ways. In this work, we consider automatically encoding two qubits into one four-state ququart via a compression scheme. We use quantum optimal control to design efficient proof-of-concept gates that fully replicate standard qubit computation on these encoded qubits.

compilation↗
DOE OSTI2023

ERF: Energy Research and Forecasting

The Energy Research and Forecasting (ERF) code is a new model that simulates the mesoscale and microscale dynamics of the atmosphere using the latest high-performance computing architectures. It employs hierarchical parallelism using an MPI+X model, where X may be OpenMP on multicore CPU-only systems, or CUDA, HIP, or SYCL on GPU-accelerated systems. ERF is built on AMReX (Zhang et al., 2019, 2021), a block-structured adaptive mesh refinement (AMR) software framework that provides the underlying performance-portable software infrastructure for block-structured mesh operations. The "energy" aspect of ERF indicates that the software has been developed with renewable energy applications in mind. In addition to being a numerical weather prediction model, ERF is designed to provide a flexible computational framework for the exploration and investigation of different physics parameterizations and numerical strategies, and to characterize the flow field that impacts the ability of wind turbines to extract wind energy. The ERF development is part of a broader effort led by the US Department of Energy's Wind Energy Technologies Office.

17 WIND ENERGY↗
DOE OSTI2020

Dakota A Multilevel Parallel Object-Oriented Framework for Design Optimization Parameter Estimation Uncertainty Quantification and Sensitivity Analysis: Version 6.12 Theory Manual

The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a theoretical manual for selected algorithms implemented within the Dakota software. It is not intended as a comprehensive theoretical treatment, since a number of existing texts cover general optimization theory, statistical analysis, and other introductory topics. Rather, this manual is intended to summarize a set of Dakota-related research publications in the areas of surrogate-based optimization, uncertainty quantification, and optimization under uncertainty that provide the foundation for many of Dakota's iterative analysis capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization Parameter Estimation Uncertainty Quantification and Sensitivity Analysis: Version 6.12 User's Manual

The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a user's manual for the Dakota software and provides capability overviews and procedures for software execution, as well as a variety of example studies.

97 MATHEMATICS AND COMPUTING↗