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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Dynamic analysis of fully constrained Cable-Driven Parallel Robots for automated prefabricated component installation

This paper presents a dynamic analysis and validation framework to assess a fully constrained six-anchor Cable-Driven Parallel Robot (CDPR) for automated installation of prefabricated facade components. Compared with conventional eight-anchor systems, the six-anchor configuration simplifies setup and reduces cost, but it also reduces control authority, shrinks the wrench-feasible workspace, and tightens orientation limits. Consequently, it is unclear a priori whether dynamically feasible trajectories exist to move the end effector from pickup to the facade. A constrained trajectory optimization is formulated to enforce the system dynamics, cable-tension bounds, and pose/velocity limits, and the framework is evaluated in simulation at three levels: (i) an idealized reference model, (ii) a lab-scale prototype model incorporating measured anchor misalignments and identified damping, and (iii) a full-scale three-story building model with load decomposition for structural feasibility checks. Across these scenarios, the analysis shows that optimal, constraint-satisfying trajectories exist that move the end effector from pickup to installation while maintaining a near-plumb, level orientation at the final pose. Collectively, this multi-scale dynamic analysis and validation framework supports the deployment readiness of the six-anchor CDPR and provides a prototype-based sensitivity case study of how measured anchor placement deviations affect feasibility.

CDPR↗
DOE OSTI2021

Interfacial thermal conductance between multi-layer graphene sheets and solid/liquid octadecane: A molecular dynamics study

Mixtures of paraffin and carbon nanofillers have promising potential for thermal storage, as paraffin (the matrix) possesses high latent heat and the nanofillers compensate for the low thermal conductivity (TC) of paraffin. Understanding thermal transport in these materials is essential for practical applications, as weak thermal transport hinders fast charge/discharge of thermal energy. Here, we use non-equilibrium molecular dynamics (NEMD) simulations to study the interfacial thermal conductance (ITC) between graphene sheets and octadecane (C18H38) matrix under the limiting conditions of the sheets being parallel or perpendicular to the direction of the imposed heat flux. The findings show that the systems containing thin graphene layers exhibit higher values of ITC. This study captures the asymptotic saturation of thermal conductance for the liquid phase of the perpendicular structure. Besides, given the greater number of structured layers of paraffin upon phase change, the ITC for the solid paraffin-graphene system is higher than the conductance of the liquid paraffin-graphene interface. We use the Pearson correlation coefficients of the vibrational power spectrum (VPS) of interfacing materials to explain the orders of magnitude variations of the observed ITC.

25 ENERGY STORAGE↗
DOE OSTI2020

An accelerated approach to inline non-LTE modeling

A goal across many physics and engineering disciplines is to use radiation-hydrodynamics codes to accurately simulate systems that are expected to deviate from local thermodynamic equilibrium (LTE), such as laser-driven hohlraums, stellar coronae, and supernova ejecta. The computational expense of traditional non-LTE (NLTE) opacity calculations can dominate the cost of simulating these systems and render NLTE physics untenable in most cases. In this paper, we present a new parallel implementation for NLTE opacity calculations that employs advanced load balancing, vectorization, and memory management to significantly reduce the computational costs of these calculations. Using the radiation-hydrodynamics code xRAGE , we demonstrate this new implementation on three test problems and present order-of-magnitude speed improvements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Immortal rays: Rethinking random ray neutron transport on GPU architectures

The Random Ray Method (TRRM) is a recently developed adaptation of the Method of Characteristics for neutral particle transport simulations. TRRM has demonstrated excellent performance on 3D nuclear reactor benchmark problems using CPU-based compute systems. When porting to GPU-based systems, however, new performance challenges arise that are unique to processors targeting massive fine-grained parallelism. For smaller problems, or for large problems that are domain decomposed across many computational nodes, the problem size per node has insufficient parallelism to saturate GPU node resources, thus greatly limiting speedup. In this study, we report on a newly developed “immortal ray” variant of TRRM. Here, the immortal ray technique exposes significantly more fine-grained parallelism by fundamentally reformulating the numerical details of ray discretization, resulting in performance tradeoffs with significant overall benefit on GPUs. For very small 2D simulation problems we found the new immortal ray variant allowed for up to a 4.4x speedup when run on a single GPU. For larger 3D simulation problems we found the new variant improved strong scaling by 3x when run on the Summit supercomputer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Enhanced quantum state transfer by circumventing quantum chaotic behavior

The ability to realize high-fidelity quantum communication is one of the many facets required to build generic quantum computing devices. In addition to quantum processing, sensing, and storage, transferring the resulting quantum states demands a careful design that finds no parallel in classical communication. Existing experimental demonstrations of quantum information transfer in solid-state quantum systems are largely confined to small chains with few qubits, often relying upon non-generic schemes. Here, by using a superconducting quantum circuit featuring thirty-six tunable qubits, accompanied by general optimization procedures deeply rooted in overcoming quantum chaotic behavior, we demonstrate a scalable protocol for transferring few-particle quantum states in a two-dimensional quantum network. These include single-qubit excitation, two-qubit entangled states, and two excitations for which many-body effects are present. Our approach, combined with the quantum circuit’s versatility, paves the way to short-distance quantum communication for connecting distributed quantum processors or registers, even if hampered by inherent imperfections in actual quantum devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Architecture, catalysis and regulation of methylthio-alkane reductase for bacterial sulfur acquisition from volatile organic compounds

Bacteria utilize methylthio-alkane reductase (MAR) to acquire sulfur from volatile organic sulfur compounds. Reductive cleavage of methylthio-ethanol and dimethylsulfide liberates methanethiol for methionine synthesis and concomitantly releases ethylene and methane, respectively. Here we show that the native MAR of Rhodospirillum rubrum is a two-component system composed of a MarH ATP-dependent reductase and a MarDK catalytic core, whose architecture parallels nitrogenase. MarS complexes with MarDK to downregulate MAR activity during cellular sulfate influx, based on chromatographic and activity analyses. MarDK possesses complex metallocofactors resembling, but not identical to, nitrogenase P- and iron-only M-clusters, designated as mar1 and mar2 clusters based on metal, spectroscopic and mutagenesis analyses. They exhibit electronic features similar to the iron-only nitrogenase under turnover and, remarkably, are matured by MarB or nitrogenase NifB, resulting in maturase-dependent activity profiles. Altogether, this suggests a broader scope of reactivity, mechanisms and regulation in microbial metabolism for the nitrogenase-like family of enzymes than previously considered.

09 BIOMASS FUELS↗
DOE OSTI2024

Force Field X: A computational microscope to study genetic variation and organic crystals using theory and experiment

Force Field X (FFX) is an open-source software package for atomic resolution modeling of genetic variants and organic crystals that leverages advanced potential energy functions and experimental data. FFX currently consists of nine modular packages with novel algorithms that include global optimization via a many-body expansion, acid–base chemistry using polarizable constant-pH molecular dynamics, estimation of free energy differences, generalized Kirkwood implicit solvent models, and many more. Applications of FFX focus on the use and development of a crystal structure prediction pipeline, biomolecular structure refinement against experimental datasets, and estimation of the thermodynamic effects of genetic variants on both proteins and nucleic acids. The use of Parallel Java and OpenMM combines to offer shared memory, message passing, and graphics processing unit parallelization for high performance simulations. Overall, the FFX platform serves as a computational microscope to study systems ranging from organic crystals to solvated biomolecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A Hybrid Data-Driven and Model-Based Anomaly Detection Scheme for DER Operation

This paper proposes a hybrid data and model-based anomaly detection scheme to secure the operation of distributed energy resources (DERs) in distribution grids. Data-driven autoencoders are set up at the edge device level and they use local DER operational data as inputs. The abnormal statuses are detected by analyzing reconstruction errors. In parallel, modelbased state estimation (SE) is set up at the central level and it uses system-wide models and measurements as data inputs. The anomalies are identified by analyzing measurement residuals. The hybrid scheme preserves the benefits of both data-driven and model-based analyses and thus improves the robustness and the accuracy of anomaly detection. Numerical tests based on the model of a real distribution feeder in Southern California highlight the proposed scheme's effectiveness and benefits.

anomaly detection↗
DOE OSTI2025

Dual transposon sequencing profiles the genetic interaction landscape in bacteria

Gene redundancy complicates systematic characterization of gene function as single-gene deletions may not produce discernible phenotypes. We report dual transposon sequencing (dual Tn-seq), a platform for assaying the fitness of a comprehensive double mutant pool in parallel. Dual Tn-seq couples random barcode transposon site sequencing with the Cre-lox system, enabling deep sampling of 73% of the 1.3 million possible double gene deletions in Streptococcus pneumoniae. The genetic interactions identified span a wide range of biochemical processes, revealing new factors in presumably well-studied pathways, exemplified by a cytidine triphosphate synthase PyrJ. Moreover, this approach should permit further investigation of growth condition–specific genetic interactions. Because dual Tn-seq does not require the construction of a large array of single mutants, it should be readily adaptable to various microorganisms.

CTP synthesis↗
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 OSTI2024

Biomolecular and Characterization Imaging Science Program: 2023 Principal Investigator Meeting Proceedings

The 2023 U.S. Department of Energy (DOE) Biological and Environmental Research (BER) program’s Biomolecular Characterization and Imaging Science (BCIS) Principal Investigator Meeting expanded in scope from previous Bioimaging Science Program (BSP) meetings to include BER Structural Biology and Imaging Resources, which are located largely at DOE Office of Science national laboratories. The BCIS meeting was part of BER’s Biological Systems Science Division (BSSD) annual PI meeting, which was held April 17–19, 2023, and featured parallel meetings of the BCIS and Genomic Science programs (GSP). The meetings were held together to encourage networking and idea exchange across technologies and biological application areas, forging new multidisciplinary collaborations among researchers from adjacent BSSD programmatic areas. Two joint BCIS-GSP sessions were held: “BCIS Technologies for Investigating the Rhizosphere” and “Joint Emerging Topics and Technologies.” The rhizosphere session focused on scientific findings from BCIS and GSP PIs, including national laboratory collaborations. The intent was to identify new opportunities to measure and understand the complex community of microbes, roots, and soils that support plant growth under challenging environmental conditions. The emerging technologies session highlighted forward-looking approaches and tools to tackle challenges within the scope of BSSD research on investigating and modifying genomic and molecular function. A final interactive discussion of the BCIS program was led by plenary session chairs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Climate Model Output Rewriter

The Climate Model Output Rewriter (CMOR) software was first developed by LLNL’s PCMDI program in early 2000s and was formally released with v1.0 (July 2006), v2.0 (January 2011), and v3.1(June 2016). CMOR is used to produce Climate and Forecast Convention (http://cfconventions.org/) CF-compliant netCDF files, in the standard format required to satisfy the World Climate Research Program (WCRP) Coupled Model Intercomparison Project (CMIP). The software has been used across multiple phases of the Earth System Modeling (ESM) project CMIP (CMIP3, CMIP5, CMIP6, and planned use in CMIP7) along with numerous parallel projects focused on preparation observations for use in model evaluation (obs4MIPs) and forcing datasets (input4MIPs) to guide ESM simulations to meet strict experimental protocols. More information can be obtained from the CMOR website and code repositories: https://cmor.llnl.gov/; https://github.com/pcmdi/cmor; https://github.com/PCMDI/cmor3_documentation The ESM variable definitions used as input for CMOR can also be viewed in code repositories: https://github.com/PCMDI/cmip3-cmor-tables/; https://github.com/PCMDI/cmip5-cmor-tables/; https://github.com/PCMDI/cmip6-cmor-tables/

Mauzey, ChristopherF↗
DOE OSTI2022

Designing for Zero Energy and Zero Carbon on a Multi-Building Scale Using URBANopt: Preprint

Groundbreaking efforts are necessary to mitigate contributors increasing impacts of climate change. In parallel to inventing pioneering clean energy technologies it is even more fundamental to rethink designing energy systems within a singular facility and collectively to function as a district. Facilities should not be continuously passive by just consuming; there is a need to shift to perform more dynamically. Designing for zero energy and zero carbon on a multi-building scale can uncover opportunities for building energy efficiency, decarbonization, demand flexibility, and resiliency that are not accessible at an individual building scale. This approach can be challenging without innovative tools to evaluate the multitude of possibilities. As an investigated result, we highlight the use of a campus-scale energy modeling platform - URBANopt™ - for the expansion of the National Renewable Energy Laboratory's (NREL's) South Table Mountain campus in Golden, Colorado. Programmatic growth included the design of three new all-electric, zero-energy, and zero-carbon, mixed used buildings (a combination of research laboratories and office space). This investigation is critical to NREL reaching net-zero emissions for its operational footprint, which will occur in phases over the next decade. Leveraging URBANopt's capabilities, we evaluate 1) high-performance building energy efficiency and decarbonization measures, 2) 4th generation district heating and cooling (4th GDHC) systems, 3) optimized onsite generation and energy storage assets that meet zero-energy and zero-carbon targets at minimum life-cycle costs, and 4) cost-optimal distributed energy technology mixes, dispatch strategies, and associated capacities that increase resiliency to grid outages. This work demonstrates the use and capabilities of URBANopt through a real-world case study on a multi-building scale.

community energy model↗
DOE OSTI2024

Thermodynamic Limits of Redox-Based Thermochemical Processes (REDOTHERM)

Solar thermochemical fuel production is a potential pathway for the production of sustain liquid drop-in fuels, which can help decarbonize the aviation and maritime sectors. In an attempt to analyze the commercial viability of this technology, several studies have been conducted, including system and technoeconomic analysis (TEA) modeling. However, most studies to date simply assume a given redox reactor efficiency, which is significantly higher than demonstrated values to date. While it is widely recognized that utilizing a counter-current flow (CF) configuration could increase the redox reactor efficiency, an over-simplification in the thermodynamic modeling may lead to unphysical results which has been included in multiple publications. The fact that the solar redox reactor is the least developed component in the process chain makes it hard to identify technology gaps and evaluate pathways to deployment at scale using this approach. In this work, a thermodynamic model for a moving oxide system has been developed, in a general form that allows to analyze the system for different redox-active materials, under a wide range of operating conditions, for both parallel and countercurrent flows. The model capabilites are demonstrated, and the model's code will be shared as an open-source on GitHub in the next few months.

chemical looping↗
DOE OSTI2023

Scaled ILU Smoothers for Navier-Stokes Pressure Projection

Incomplete LU (ILU) smoothers are effective in the algebraic multigrid (AMG) V-cycle for reducing high-frequency components of the error. However, the requisite direct triangular solves are comparatively slow on GPUs. Previous work has demonstrated the advantages of Jacobi iteration as an alternative to direct solution of these systems. Depending on the threshold and fill-level parameters chosen, the factors can be highly nonnormal and Jacobi is unlikely to converge in a low number of iterations. We demonstrate that row scaling can reduce the departure from normality, allowing us to replace the inherently sequential solve with a rapidly converging Richardson iteration. There are several advantages beyond the lower compute time. Scaling is performed locally for a diagonal block of the global matrix because it is applied directly to the factor. Further, an ILUT Schur complement smoother maintains a constant GMRES iteration count as the number of MPI ranks increases, and thus parallel strong-scaling is improved. Our algorithms have been incorporated into hypre, and we demonstrate improved time to solution for linear systems arising in the Nalu-Wind and PeleLM pressure solvers. For large problem sizes, GMRES+AMG executes at least five times faster when using iterative triangular solves compared with direct solves on massively parallel GPUs.

algebraic multigrid↗
DOE OSTI2021

Impact of Blockchain Delay on Grid-Tied Solar Inverter Performance

This paper investigates the impact of the delay resulting from a blockchain, a promising security measure, for a hierarchical control system of inverters connected to the grid. The blockchain communication network is designed at the secondary control layer for resilience against cyberattacks. To represent the latency in the communication channel, a model is developed based on the complexity of the blockchain framework. Taking this model into account, this work evaluates the plant’s performance subject to communication delays, introduced by the blockchain, among the hierarchical control agents. In addition, this article considers an optimal model-based control strategy that performs the system’s internal control loop. The work shows that the blockchain’s delay size influences the convergence of the power supplied by the inverter to the reference at the point of common coupling. In the results section, real-time simulations on OPAL-RT are performed to test the resilience of two parallel inverters with increasing blockchain complexity.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2020

STEPS: A Portable Numerical Simulation Toolkit for Electrical Power System Dynamic Studies

Numerical simulation is the key technique for large scale power system analysis. Redistribution of global renewable power via international interconnections requires new simulation tools to study the interconnected systems with different nominal frequencies as a whole. In this paper we introduce an open source simulation toolkit for electrical power systems (STEPS) which is hosted at Github. Its kernel is coded in C++ with major functions of power flow and electro-mechanical dynamic simulation. Flexible options are provided and configurable to improve power flow solution and dynamic simulation. Common devices and models are supported in STEPS for AC/DC hybrid system studies. Studies of interconnected systems with different nominal frequencies is supported in STEPS for research of international interconnection. Application program interfaces are provided and wrapped with Python to enable high-level interfaces for general applications. STEPS is thread safe and parallel computation is supported in both kernel and script levels to accelerate simulation. It is portable and works on Windows and GNU/Linux platforms. Cases from small to large scale systems are thoroughly tested to validate the toolkit with commercial packages as benchmarks.

42 ENGINEERING↗
DOE OSTI2021

An Integrated High-performance Computing and Digital Real-time Simulation Testbed to Benchmark Closed-loop Load Shedding Algorithms in Power Systems

An integrated testbed using digital real-time simulator (DRTS) and a high-performance computing (HPC) cluster is presented here to compare speed and performance of computational schemes to mitigate time-critical issues in electric power systems. The first approach in this testbed validation is taken by running a set of closed-loop load shedding algorithms to compare and contrast two paradigms of arresting cascading failure propagation. Two algorithms involve solving DC and AC power flow model-based optimization problems to compute load shedding at different buses, while a model-based stochastic search using parallel computing provides a viable alternative. The algorithms are implemented in the DRTS-HPC testbed for the IEEE 14-bus benchmark transmission system. As a proof of the concept, simulation results are presented for implementation of closed-loop load-shedding algorithms for cascading failures in the DRTS-HPC testbed

24 POWER TRANSMISSION AND DISTRIBUTION↗