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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 937 records · Page 52

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NASA NTRS1990

A network flow model for load balancing in circuit-switched multicomputers

In multicomputers that utilize circuit switching or wormhole routing, communication overhead depends largely on link contention - the variation due to distance between nodes is negligible. This has a major impact on the load balancing problem. In this case, there are some nodes with excess load (sources) and others with deficit load (sinks) and it is required to find a matching of sources to sinks that avoids contention. The problem is made complex by the hardwired routing on currently available machines: the user can control only which nodes communicate but not how the messages are routed. Network flow models of message flow in the mesh and the hypercube were developed to solve this problem. The crucial property of these models is the correspondence between minimum cost flows and correctly routed messages. To solve a given load balancing problem, a minimum cost flow algorithm is applied to the network. This permits one to determine efficiently a maximum contention free matching of sources to sinks which, in turn, tells one how much of the given imbalance can be eliminated without contention.

Bokhari, Shahid H.↗

NASA NTRS1993

A network flow model for load balancing in circuit-switched multicomputers

Bokhari, Shahid H.↗

NASA NTRS2001

Selected Contribution: Skeletal muscle focal adhesion kinase, paxillin, and serum response factor are loading dependent

This investigation examined the effect of mechanical loading state on focal adhesion kinase (FAK), paxillin, and serum response factor (SRF) in rat skeletal muscle. We found that FAK concentration and tyrosine phosphorylation, paxillin concentration, and SRF concentration are all lower in the lesser load-bearing fast-twitch plantaris and gastrocnemius muscles compared with the greater load-bearing slow-twitch soleus muscle. Of these three muscles, 7 days of mechanical unloading via tail suspension elicited a decrease in FAK tyrosine phosphorylation only in the soleus muscle and decreases in FAK and paxillin concentrations only in the plantaris and gastrocnemius muscles. Unloading decreased SRF concentration in all three muscles. Mechanical overloading (via bilateral gastrocnemius ablation) for 1 or 8 days increased FAK and paxillin concentrations in the soleus and plantaris muscles. Additionally, whereas FAK tyrosine phosphorylation and SRF concentration were increased by < or =1 day of overloading in the soleus muscle, these increases did not occur until somewhere between 1 and 8 days of overloading in the plantaris muscle. These data indicate that, in the skeletal muscles of rats, the focal adhesion complex proteins FAK and paxillin and the transcription factor SRF are generally modulated in association with the mechanical loading state of the muscle. However, the somewhat different patterns of adaptation of these proteins to altered loading in slow- vs. fast-twitch skeletal muscles indicate that the mechanisms and time course of adaptation may partly depend on the prior loading state of the muscle.

NASA Discipline Musculoskeletal↗

DOE OSTI2026

Modeling Framework for Data Center

This chapter highlights the critical need for advanced modeling of data centers due to their rapidly increasing energy consumption and impact on grid reliability. Driven by the demand for AI applications, data centers are projected to consume a significant portion of US energy by 2028, putting stress on an already challenged power grid. The chapter emphasizes the importance of "fast" time-scale models to understand the dynamic interactions between data centers and the grid, especially given the rapid power fluctuations of AI workloads. It outlines a modeling framework that includes both offline and real-time EMT domain simulations, detailing the necessary representations for various components like utility interfaces, transformers, IT loads, UPS, cooling loads, Battery Energy Storage Systems (BESS), generators, protection systems, and higher-level control systems. While standard simulation tools like PSCAD offer basic models, custom development is often required to accurately capture the unique and fast-changing behaviors of modern data centers. The chapter also discusses key metrics and test cases for validating these models, focusing on transient load responses, protection relay coordination, and demand flexibility. Finally, it addresses the challenges of modeling large-scale data centers, such as computational complexity and the trade-off between model fidelity and practicality, suggesting hybrid modeling approaches as a solution. The overarching goal is to create a robust framework that helps assess data center impacts on grid stability, identify vulnerabilities, and inform the development of standards for reliable integration of these large loads into the bulk power system.

25 ENERGY STORAGE↗

NASA NTRS1976

Crack growth in Ti-8Al-1Mo-1V with real-time and accelerated flight-by-flight loading

Crack growth in Ti-8Al-1Mo-1V was measured and calculated for real-time and accelerated simulations of supersonic airplane loading and heating. Crack-growth rates calculated on the assumption that an entire flight could be represented by a single cycle predicted the experimental rates poorly. Calculated crack-growth rates were slower than the experimental rates for all tests with flight-by-flight loading. For room-temperature accelerated tests, the calculated rates agreed well with the experimental rates; but the calculations became progressively less accurate for progressively more complex test conditions (tests that included elevated temperature). Calculations of crack growth using the crack-closure concept can probably be improved through study of crack-opening stresses using finite-element models that account for variable-amplitude loading, residual stresses, and temperature effects. The calculations of crack growth could also be improved through detailed studies of material properties and interactions among stress, temperature, and time as appropriate for the real-time operating conditions of a supersonic transport airplane.

Imig, L. A.↗

DOE OSTI2019

Surface complexation model of rare earth element adsorption onto bacterial surfaces with lanthanide binding tags

© 2019 Elsevier Ltd Lanthanide binding tags (LBTs) have been engineered onto the cell surface of E. coli to enhance biosorption and recovery of rare earth elements (REEs). The protonation behavior of the bacterial surfaces before and after LBT-display was compared by modeling acid-base titration data. A multiple discrete site, constant capacitance surface complexation model was constructed to examine rare earth (Tb) binding to cell surface functional groups, comparing wild type and LBT-engineered surfaces. Our acid-base titrations show similar pKa values between the two strains, suggesting induction of LBTs does not significantly alter cell surface protonation behavior. Tb sorption onto the wild type cell surface can be captured by a one-site carboxyl model. The LBT strain exhibited a higher metal loading that can be explained by the increase of sorption sites in the form of lanthanide binding tags. Furthermore, carboxyl site concentrations between wild type and LBT-induced cells were statistically indistinguishable. We thus attribute the engineered strains’ increase in Tb adsorption capacity and affinity to the addition of lanthanide binding tags to the cell surface. The Tb stability constant with the LBT site is two orders of magnitude higher than that with the carboxyl functional group. As a result, at low metal loading <10 μM, the Tb binding to the cell surface of the LBT-strain is controlled by the presence of high-affinity, but lower capacity, LBT sites. At higher metal loadings >10 μM, a more abundant but low affinity functional group becomes the main source of adsorption that results in an overall higher sorption capacity. This work demonstrates how surface complexation modeling can be implemented for bacterial surfaces engineered with a known protein tag to optimize REE recovery from fluids with variable pH and metal loadings.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

Control and data acquisition upgrades for NSTX-U

The extensive NSTX Upgrade (NSTX-U) Project includes major components which allow a doubling of the toroidal field strength to 1 T, of the Neutral Beam heating power to 12 MW, and the plasma current to 2 MA, and substantial structural enhancements to withstand the increased electromagnetic loads. The maximum pulse length will go from 1.5 to 5 s. The larger and more complex forces on the coils will be protected by a Digital Coil Protection System, which requires demanding real-time data input rates, calculations and responses. The amount of conventional digitized data for a given pulse is expected to increase from 2.5 to 5 GB per second of pulse. 2-D Fast Camera data is expected to go from 2.5 GB/pulse to 10, and another 2 GB/pulse is expected from new IR cameras. Our network capacity will be increased by a factor of 10, with 10 Gb/s fibers used for the major trunks. 32-core Linux systems will be used for several functions, including between-shot data processing, MDSplus data serving, between-shot EFIT analysis, real-time processing, and for a new capability, between-shot TRANSP. As a result, improvements to the MDSplus events subsystem will be made through the use of both UDP and TCP/IP based methods and the addition of a dedicated “event server”.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

The pervasive impact of critical fluctuations in liquid–liquid extraction organic phases

Liquid-liquid extraction is an essential chemical separation technique where polar solutes are extracted from an aqueous phase into a nonpolar organic solvent by amphiphilic extractant molecules. A fundamental limitation to the efficiency of this important technology is third phase formation, wherein the organic phase splits upon sufficient loading of polar solutes. The nanoscale drivers of phase splitting are challenging to understand in the complex hierarchically structured organic phases. In this study, we demonstrate that the organic phase structure and phase behavior are fundamentally connected in a way than can be understood with critical phenomena theory. For a series of binary mixtures of trialkyl phosphate extractants with linear alkane diluents, we combine small angle x-ray scattering and molecular dynamics simulations to demonstrate how the organic phase mesostructure over a wide range of compositions is dominated by critical concentration fluctuations associated with the critical point of the third phase formation phase transition. These findings reconcile many longstanding inconsistencies in the literature where small angle scattering features, also consistent with such critical fluctuations, were interpreted as reverse micellar-like particles. Altogether, this study shows how the organic phase mesostructure and phase behavior are intrinsically linked, deepening our understanding of both and providing a new framework for using molecular structure and thermodynamic variables to control mesostructure and phase behavior in liquid-liquid extraction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Phasor-Based Adaptive Control of a Test-Feeder Distribution Network

Control in the power distribution system is needed to match the generation of electricity (that is, supply) with the demand for power (that is, load) at all times while maintaining a high level of power quality [1] (see "Summary"). The complexity of controlling the electric distribution system increases when distributed intermittent energy sources, such as solar photovoltaics (PVs), displace large-scale dispatchable generation [2]-[10]. Furthermore, if the supply from distributed resources exceeds the time-varying demand across a feeder, then the feeder-level voltage will increase. In extreme cases, large voltage increases will trigger the disconnection of distributed generation to protect electrical equipment and ensure customer safety. Consequently, coordinating renewable energy sources that are distributed throughout the distribution system-to match real-time demand across an entire power network-brings the additional challenge of maintaining a high level of supply reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

MoorDyn V2: New Capabilities in Mooring System Components and Load Cases

MoorDyn, an open-source mooring dynamics model, is being expanded with capabilities for additional mooring system features and load cases. As floating wind turbine technology matures, mooring systems are becoming more sophisticated and more complex scenarios need to be considered in the design process. Mooring systems may have synthetic line materials, ballast/buoyancy bodies along the lines, or interconnections between platforms. Failure modes may involve multiple cascading line failures that depend on mooring system dynamics. Features recently added to MoorDyn aim to address these emerging needs. MoorDyn’s linear elasticity model has been supplemented to support user-defined stress-strain curves, which can be adjusted to represent synthetic mooring materials. Rigid six-degree-of-freedom bodies in the mooring system can now be modeled using two new model objects. “Rod” objects provide an option for rigid cylindrical bodies. They use the existing Morison equation-based hydrodynamics model and can be connected to mooring lines at either end. “Body” objects provide a generic six-degree-of-freedom rigid-body representation based on a lumped-parameter model of translational and rotational properties. Rod objects can be added to Body objects and mooring lines can be attached at any location, allowing a wide variety of submerged structures to be integrated into the mooring system. Lastly, a means of dynamically simulating mooring line failures has been implemented. These new features, currently in the C++ version of MoorDyn, are described and then demonstrated on a two-turbine shared-mooring array. A qualitative view of the results suggests the new features are functioning as expected.

49 EE - Wind and Water Power Program - Wind (EE-4W↗

DOE OSTI2020

Improving High-Energy Particle Detectors with Machine Learning

Microseconds after the Big Bang, the universe existed in a state called the quark-gluon plasma (QGP). To experimentally study its properties, the QGP is recreated in high-energy nuclear collisions at the LHC, and the particles produced from the QGP are reconstructed from their energy deposition in the ATLAS calorimeter. This requires both classifying the particles and calibrating their deposited energy. The objective of this project is to improve the reconstruction by using machine learning techniques, where the energy depositions of clusters of cells, formed by ATLAS topo-clustering methods, are treated as three-dimensional images when inputted to neural networks. This approach significantly improves the calibration of deposited energies when cross-validating while training, and models trained on idealized data predict the calibrated energies of particles in more complex data sets well. Additionally, implementation of a data generator using uproot allows the program to load input data into memory as needed while training or predicting, significantly reducing the amount of memory used. The data generator also allows for use of multiprocessing to speed up training and evaluating. This work illustrates that using machine learning methods for both classification and calibration has the potential to significantly improve particle reconstruction.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Overview of Proposed Summer Project [Slides]

The following are visual aids developed to assist in initial discussion with an intern about their proposed Summer 2021 project. Project Goal: Develop a user friendly code to assess pressure load on a geometry of interest to understand the rigid body effects, and compare to more complex approaches

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Reactor Physics Simulations of the High Flux Isotope Reactor Permanent Beryllium Reflector Number 5 Design

This study evaluates reactor physics aspects of the proposed High Flux Isotope Reactor (HFIR) permanent beryllium reflector number 5 design. HFIR is a pressurized, light water–cooled, and beryllium reflected research reactor that operates at 85 MW for cycle lengths of approximately 24 to 26 days. A new permanent reflector design is highly desirable for increased versatility in irradiation experiments, to arrange the vertical experiment facilities (VXFs) to minimize their impact on neutron scattering if loaded with neutronabsorbing experiments, to enhance reflector thermal-structural-hydraulic performance, and to simplify the complex fabrication process. The current number 4 and concept number 5 reflectors have 22 and 28 VXFs, respectively, and are modeled and analyzed in this study with the MCNP5 and SCALE 6.1.3 nuclear simulation codes.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

Explainable and Differentiable Reinforcement Learning for Multi-objective Optimization in Particle Accelerators

Operating particle accelerators involves optimizing multiple goals simultaneously, which can be challenging due to trade-offs among objectives. While evolutionary algorithms like the genetic algorithm (GA) have been used for various Multi-Objective Optimization (MOO) tasks, they are not inherently suited for complex control problems. This talk highlights two variations of Reinforcement Learning (RL) for concurrently optimizing heat load and trip rates at the Continuous Electron Beam Accelerator Facility (CEBAF). The problem involves strict constraints on individual states, actions, and overall energy requirements of the beam. First, this talk highlights how differentiability can be harnessed through a Deep Differentiable Reinforcement Learning (DDRL) approach to address MOO issues within particle accelerators. We examine the DDRL method alongside Model Free Reinforcement Learning (MFRL), GA, and Bayesian Optimization (BO). The performance of these methods is assessed by generating a Pareto-front for two objectives. Our findings indicate that DDRL excels in handling high-dimensional problems more effectively than MFRL, BO, and GA. Next, we will show integration of explainable physics-based constraints into RL algorithms to enhance trans- parency and trust in decision-making processes by enabling users to verify that agents adhere to established physical principles. This surrogate function can be modeled using neural networks or sparse dictionary mod- els. By examining the mathematical form of the learned constraint function, we are able to confirm the agent has learned to use the established physics of each environment provided but the surrogate model. In addi- tion, we find that the introduction of a mathematical functional dictionary based surrogate model enables our reinforcement learning algorithms to reliably converge for difficult high-dimensional accelerator controls environments.

Rajput, Kishansingh [Thomas Jefferson National Acc↗

DOE OSTI2024

Simulation of the Multi-Wake Evolution of Two Sandia National Labs/National Rotor Testbed Turbines Operating in a Tandem Layout

The future of wind power systems deployment is in the form of wind farms comprised of scores of such large turbines, most likely at offshore locations. Individual turbines have grown in span from a few tens of meters to today’s large turbines with rotor diameters that dwarf even the largest commercial aircraft. These massive dynamical systems present unique challenges at scales unparalleled in prior applications of wind science research. Fundamental to this effort is the understanding of the wind turbine wake and its evolution. Furthermore, the optimization of the entire wind farm depends on the evolution of the wakes of different turbines and their interactions within the wind farm. In this article, we use the capabilities of the Common ODE Framework (CODEF) model for the analysis of the effects of wake–rotor and wake-to-wake interactions between two turbines situated in a tandem layout fully and partially aligned with the incoming wind. These experiments were conducted in the context of a research project supported by the National Rotor Testbed (NRT) program of Sandia National Labs (SNL). Results are presented for a layout which emulates the turbine interspace and relative turbine emplacement found at SNL’s Scaled Wind Technologies Facility (SWiFT), located in Lubbock, Texas. The evolution of the twin-wake interaction generates a very rich series of secondary transitions in the vortex structure of the combined wake. These ultimately affect the wake’s axial velocity patterns, altering the position, number, intensity, and shape of localized velocity-deficit zones in the wake’s cross-section. This complex distribution of axial velocity patterns has the capacity to substantially affect the power output, peak loads, fatigue damage, and aeroelastic stability of turbines located in subsequent rows downstream on the farm.

Baruah, Apurva (ORCID:0000000252354068)↗

DOE OSTI2026

Environmental Durability Assessment and Development of Subcomponent Test Methods for Advanced Materials in Marine Energy Applications

Marine energy developers are beginning to rely more heavily on advanced composite materials for their load-bearing structures. Understanding how these materials respond and degrade in harsh marine environments is a complex problem. Much research has been performed at smaller laboratory scales to understand the fundamental physical and chemical degradation mechanisms, but little structural testing research has been performed at larger scales to understand how these physical and chemical interactions scale and how they should be accounted for in the design process. The Advanced Materials project is a multilaboratory research collaboration that addresses these issues with the intention of reducing risks and barriers to marine energy developers wanting to adopt advanced composite materials. The National Laboratory of the Rockies has been playing a leading role in developing larger-scale testing infrastructure and test methods to validate complex numerical degradation models and standardize testing procedures to do so. This paper reviews past structural testing activities, how they have grown into current research activities, and how they will continue to evolve to directly address industry needs. This paper covers key research areas - large-scale water absorption and subsequent structural validation testing, qualification of bolted and adhesive connections, and combined submerged fatigue testing at increasing scales. It provides insights into the complex requirements for testing infrastructure and test method development to effectively qualify materials and certify marine energy structures for harsh marine environments. This research program paves the way for better guidance and standardization within the industry when adopting advanced composite materials.

16 TIDAL AND WAVE POWER↗

NASA NTRS1969

On the shell equations in complex form.

Linear thin shell theory in complex dependent variable form for determining fourth order partial differential equations, considering elastic shells with edge loads

Sanders, J. L., Jr.↗

NASA NTRS1972

Computerized multilevel analysis for multilayered fiber composites

A FORTRAN 4 computer code for the micromechanics, macromechanics, and laminate analysis of multilayered fiber composite structural components is described. The code can be used either individually or as a subroutine within a complex structural analysis/synthesis program. The inputs to the code are constituent materials properties, composite geometry, and loading conditions. The outputs are various properties for ply and composite; composite structural response, including bending-stretching coupling; and composite stress analysis, including comparisons with failure criteria for combined stress. The code was used successfully in the analysis and structural synthesis of flat panels, in the buckling analysis of flat panels, in multilayered composite material failure studies, and lamination residual stresses analysis.

Chamis, C. C.↗