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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 1,333 records · Page 74

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NASA NTRS1989

An integrated methodology for optimizing structural composite damping

A method is presented for tailoring plate and shell composite structures for optimal forced damped dynamic response. The damping of specific vibration modes is optimized with respect to dynamic performance criteria including placement of natural frequencies and minimization of resonance amplitudes. The structural composite damping is synthesized from the properties of the constituent materials, laminate parameters, and structural geometry based on a specialty finite element. Application studies include the optimization of laminated composite beams and composite shells with fiber volume ratios and ply angles as design variables. The results illustrate the significance of damping tailoring to the dynamic performance of composite structures, and the effectiveness of the method in optimizing the structural dynamic response.

Saravanos, D. A.↗

NASA NTRS1990

An integrated methodology for optimizing the passive damping of composite structures

Saravanos, D. A.↗

DOE OSTI2024

Underestimation of multi-decadal global O 2 loss due to an optimal interpolation method

Abstract. The global ocean's oxygen content has declined significantly over the past several decades and is expected to continue decreasing under global warming, with far-reaching impacts on marine ecosystems and biogeochemical cycling. Determining the oxygen trend, its spatial pattern, and uncertainties from observations is fundamental to our understanding of the changing ocean environment. This study uses a suite of CMIP6 Earth system models to evaluate the biases and uncertainties in oxygen distribution and trends due to sampling sparseness. Model outputs are sub-sampled according to the spatial and temporal distribution of the historical shipboard measurements, and the data gaps are filled by a simple optimal interpolation method using Gaussian covariance with a constant e-folding length scale. Sub-sampled results are compared to full model output, revealing the biases in global and basin-wise oxygen content trends. The simple optimal interpolation underestimates the modeled global deoxygenation trends, capturing approximately two-thirds of the full model trends. The North Atlantic and subpolar North Pacific are relatively well sampled, and the simple optimal interpolation is capable of reconstructing more than 80 % of the oxygen trend in the non-eddying CMIP models. In contrast, pronounced biases are found in the equatorial oceans and the Southern Ocean, where the sampling density is relatively low. The application of the simple optimal interpolation method to the historical dataset estimated the global oxygen loss to be 1.5 % over the past 50 years. However, the ratio of the global oxygen trend between the sub-sampled and full model output has increased the estimated loss rate in the range of 1.7 % to 3.1 % over the past 50 years, which partially overlaps with previous studies. The approach taken in this study can provide a framework for the intercomparison of different statistical gap-filling methods to estimate oxygen content trends and their uncertainties due to sampling sparseness.

Ito, Takamitsu (ORCID:000000019873099X)↗

NASA NTRS1991

Use of mercuric iodide X-ray detectors with alpha backscattering spectrometers for space applications

The authors present X-ray fluorescence (XRF) spectra of different extraterrestrial samples taken with a mercuric iodide (HgI2) spectrometer inserted into an alpha backscattering instrument identical to that used in the Soviet Phobos mission. The results obtained with the HgI2 ambient temperature detector are compared with those obtained using an Si(Li) cryogenically cooled detector. Efforts to design an optimized instrument for space application are also described. The results presented indicate that the energy resolution and sensitivity of HgI2 detectors are adequate to meet the performance needs of a number of proposed space applications, particularly those in which cooled silicon X-ray detectors are impractical or even not usable, such as for the target science programs on geoscience opportunities for lunar surface, Mars surface, and other comet and planetary missions being planned by NASA and ESA.

Iwanczyk, J. S.↗

DOE OSTI2018

Potential Ideas for an El Capitan Center of Excellence (COE) Around Intelligent Simulation

Proposing a Center of Excellence under the CORAL-2 NRE is a mandatory requirement. The current Sierra COE (CORAL-1) is largely focused on helping LLNL applications make the disruptive transition to a heterogeneous GPU-based system by 2018. We expect a continuation of COE activities around optimizing our broad and diverse application base (of so-called “traditional” simulation codes) optimized for the El Capitan architecture, as well as supporting the underlying software stack (compilers, tools, programming models, etc.) – but do not expect this to require as much effort in the El Capitan COE (assuming a heterogeneous node architecture). What follows are some thoughts on 3 potential topics of interest for an El Capitan COE at LLNL – largely focused around AI and machine learning and the concept of advancing our goal of intelligent simulation or cognitive computing in the timeframe of deployment and production use of El Capitan (2023-2038). We believe vendor engagement through a COE in this area will provide a natural point-of-interest between LLNL and our vendor partner for common advancement of machine learning capabilities focused on scientific data – potentially greatly broadening the ecosystem around HPC architectures and the supporting software stack for scientific simulation-based AI.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2017

Temporal Planning for Compilation of Quantum Approximate Optimization Algorithm Circuits

We investigate the application of temporal planners to the problem of compiling quantum circuits to newly emerging quantum hardware. While our approach is general, we focus our initial experiments on Quantum Approximate Optimization Algorithm (QAOA) circuits that have few ordering constraints and allow highly parallel plans. We report on experiments using several temporal planners to compile circuits of various sizes to a realistic hardware. This early empirical evaluation suggests that temporal planning is a viable approach to quantum circuit compilation.

planning↗

DOE OSTI2020

CCM vs. CRM Design Optimization of a Boost-derived Parallel Active Power Decoupler for Microinverter Applications

Single-phase inverter or rectifier systems often make use of an auxiliary active power decoupler (APD) to balance the mismatch between steady DC power and fluctuating AC power. This paper deals with efficiency and size optimization of a parallel boost-type APD circuit for PV microinverter applications. Specifically, design of an eGaNFET-based, 400 W APD circuit, employing planar inductor and operating in either continuous conduction mode (CCM) or critical conduction mode (CRM) is considered. Available design variables including inductance value, inductor core geometry, capacitor voltage, switching frequency, and modulation scheme (CCM vs. CRM) are explored to identify Pareto-optimal configurations, which can achieve low California Energy Commission (CEC) efficiency drop while also reducing the footprint area of the inductor. The theoretical study predicts that the optimal CRM design can achieve 37% reduced inductor size, while operating with similar efficiency drop, compared to the optimal CCM design. Experimental results, obtained using two separate 40 V, 400 W hardware prototypes for CCM and CRM, are presented to verify the analyses.

14 SOLAR ENERGY↗

DOE OSTI2024

Multi‐Objective Optimization for Rapid Identification of Novel Compound Metals for Interconnect Applications

Abstract Interconnect materials play the critical role of routing energy and information in integrated circuits. However, established bulk conductors, such as copper, perform poorly when scaled down beyond 10 nm, limiting the scalability of logic devices. Here, a multi‐objective search is developed, combined with first‐principles calculations, to rapidly screen over 15,000 materials and discover new interconnect candidates. This approach simultaneously optimizes the bulk electronic conductivity, surface scattering time, and chemical stability using physically motivated surrogate properties accessible from materials databases. Promising local interconnects are identified that have the potential to outperform ruthenium, the current state‐of‐the‐art post‐Cu material, and also semi‐global interconnects with potentially large skin depths at the GHz operation frequency. The approach is validated on one of the identified candidates, CoPt, using both ab initio and experimental transport studies, showcasing its potential to supplant Ru and Cu for future local interconnects.

Chemistry↗

DOE OSTI2020

Phase I Final Technical Report on Energy-Efficient Reconfigurable Universal Accelerator Interconnect

It is well known that application specific computing systems, optimally designed and configured for a given workload, offer much higher energy-efficiency and throughput than general purpose systems. In modern computing systems, heterogeneous computing systems have emerged that exploit the energy and performance benefits of combining various different domain-specific processor architectures. Application domains such as high-performance computing and machine learning now process terabyte-sized data sets, requiring enormous processing and memory resources. These applications have very high-power consumption due to bottlenecks in the electrical interconnection between processing units. This project aims to reduce both communication energy and latency by integrating universally available accelerators with silicon photonics. It also aims to increase system throughput by exploiting emerging technologies in silicon photonic reconfigurable interconnects; this will allow the system to balance itself in real time to accommodate changes in workloads and data flows.

2.5D/3D integration↗

NASA NTRS2014

Preliminary Structural Design Using Topology Optimization with a Comparison of Results from Gradient and Genetic Algorithm Methods

In this paper, genetic algorithm based and gradient-based topology optimization is presented in application to a real hardware design problem. Preliminary design of a planetary lander mockup structure is accomplished using these methods that prove to provide major weight savings by addressing the structural efficiency during the design cycle. This paper presents two alternative formulations of the topology optimization problem. The first is the widely-used gradient-based implementation using commercially available algorithms. The second is formulated using genetic algorithms and internally developed capabilities. These two approaches are applied to a practical design problem for hardware that has been built, tested and proven to be functional. Both formulations converged on similar solutions and therefore were proven to be equally valid implementations of the process. This paper discusses both of these formulations at a high level.

Burt, Adam O.↗

DOE OSTI2019

The use of multi-objective optimization to improve the design process of nuclear power plant systems

Multi-objective optimization is proposed to address the problem of design optimality in the nuclear power plant design process. This is done via the creation/development of the Optimization and Preference Tool for the Improvement of Nuclear Systems (OPTIONS). This work details applications of multi-objective optimization methods (in Python 3) to two different nuclear system design problems: the flash-Rankine power conversion system (PCS) of the I 2 S-LWR and the Passive Endothermic Reaction Cooling System (PERCS) attached to a standard PWR primary system (in RELAP5). The PCS design problem is first solved for three configurations using a specific particle swarm optimization method, achieving a thermodynamic efficiency of 34.81%. A new method, the Mixed-Integer Non-dominated Sorting Genetic Algorithm (MI-NSGA), is created and then used, solving a PCS superstructure of 22 configurations and achieving an efficiency of 35.63%. Finally, the OPTIONS tool is used to optimize the PERCS, improving cost, core temperature control, and cooling longevity.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1998

Signal Analysis of Helicopter Blade-Vortex-Interaction Acoustic Noise Data

Blade-Vortex-Interaction (BVI) produces annoying high-intensity impulsive noise. NASA Ames collected several sets of BVI noise data during in-flight and wind tunnel tests. The goal of this work is to extract the essential features of the BVI signals from the in-flight data and examine the feasibility of extracting those features from BVI noise recorded inside a large wind tunnel. BVI noise generating mechanisms and BVI radiation patterns an are considered and a simple mathematical-physical model is presented. It allows the construction of simple synthetic BVI events that are comparable to free flight data. The boundary effects of the wind tunnel floor and ceiling are identified and more complex synthetic BVI events are constructed to account for features observed in the wind tunnel data. It is demonstrated that improved recording of BVI events can be attained by changing the geometry of the rotor hub, floor, ceiling and microphone. The Euclidean distance measure is used to align BVI events from each blade and improved BVI signals are obtained by time-domain averaging the aligned data. The differences between BVI events for individual blades are then apparent. Removal of wind tunnel background noise by optimal Wiener-filtering is shown to be effective provided representative noise-only data have been recorded. Elimination of wind tunnel reflections by cepstral and optimal filtering deconvolution is examined. It is seen that the cepstral method is not applicable but that a pragmatic optimal filtering approach gives encouraging results. Recommendations for further work include: altering measurement geometry, real-time data observation and evaluation, examining reflection signals (particularly those from the ceiling) and performing further analysis of expected BVI signals for flight conditions of interest so that microphone placement can be optimized for each condition.

Rogers, James C.↗

NASA NTRS1991

Optimal design of solidification processes

An optimal design algorithm is presented for the analysis of general solidification processes, and is demonstrated for the growth of GaAs crystals in a Bridgman furnace. The system is optimal in the sense that the prespecified temperature distribution in the solidifying materials is obtained to maximize product quality. The optimization uses traditional numerical programming techniques which require the evaluation of cost and constraint functions and their sensitivities. The finite element method is incorporated to analyze the crystal solidification problem, evaluate the cost and constraint functions, and compute the sensitivities. These techniques are demonstrated in the crystal growth application by determining an optimal furnace wall temperature distribution to obtain the desired temperature profile in the crystal, and hence to maximize the crystal's quality. Several numerical optimization algorithms are studied to determine the proper convergence criteria, effective 1-D search strategies, appropriate forms of the cost and constraint functions, etc. In particular, we incorporate the conjugate gradient and quasi-Newton methods for unconstrained problems. The efficiency and effectiveness of each algorithm is presented in the example problem.

Dantzig, Jonathan A.↗

NASA NTRS1988

Singular perturbations and time scales in the design of digital flight control systems

The results are presented of application of the methodology of Singular Perturbations and Time Scales (SPATS) to the control of digital flight systems. A block diagonalization method is described to decouple a full order, two time (slow and fast) scale, discrete control system into reduced order slow and fast subsystems. Basic properties and numerical aspects of the method are discussed. A composite, closed-loop, suboptimal control system is constructed as the sum of the slow and fast optimal feedback controls. The application of this technique to an aircraft model shows close agreement between the exact solutions and the decoupled (or composite) solutions. The main advantage of the method is the considerable reduction in the overall computational requirements for the evaluation of optimal guidance and control laws. The significance of the results is that it can be used for real time, onboard simulation. A brief survey is also presented of digital flight systems.

Naidu, Desineni S.↗

DOE OSTI2018

Toward Automated Tools for Characterization of Molecular Porosity

The emerging advanced porous materials, e.g. extended framework materials and porous molecular materials, offer an unprecedented level of control of their structure and function. The enormous possibilities for tuning these materials by changing their building blocks mean that, in principle, optimally performing materials for a variety of applications can be systematically designed. However, the process of finding a set of optimal structures for a given application requires computational high-throughput tools to analyze and sieve through many candidate materials. In particular, in the case of porous molecular materials, the analysis and selection of a molecule is one of the key aspects as the structure of the molecule determines the structure of the resulting material, and very often the porosity of the molecule significantly contributes to the porous properties of the resulting material. In this work, we introduce definitions and algorithms to characterize porosity at the molecular level, along with a software implementation of these algorithms. We demonstrate applications of the software tool in the discovery and characterization of porous molecules among ca. 94 million molecules currently enlisted in the PubChem database.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

A Strawman for an HPC PowerStack

The landscape of High-Performance Computing (HPC) is changing as we enter the exascale era and power and energy management are key design points for any next generation of supercomputers. Efficiently utilizing procured power and optimizing performance of scientific applications under power and energy constraints is challenging due to several reasons including dynamic phase behavior, processor manufacturing variability and increasing heterogeneity of node-level components. Extending the scope from the node- and application-level up to the system-level introduces further challenges on top of power-unaware job scheduling, which is known to be NP-hard on its own. While there exists several individual efforts across the community to research automatic techniques for managing power and energy better, the majority of these techniques have been specialized to meet the needs of a specific HPC center or specific optimization goals and provide little support to connect them to each other. Some projects, most notably the PowerAPI efforts [1], discuss interfaces that form a good starting point for full stack integration, but these interfaces still need to be hooked up to the wide range of software components offered by academic partners, developers or vendors. Furthermore, a recent survey conducted by the EE HPC WG concluded that the majority of such techniques have lacked the application-awareness required to achieve the best system performance and throughput. Other observations were that each technique tended to target management of power and energy for a different subset of the site or system hardware and that the different techniques tended to perform management at different (and often conflicting) granularities. Unfortunately, the existing techniques have not been designed to coexist simultaneously on one site and cooperate on management in an integrated manner [2]. The lack of application-awareness, lack of coordinated management across different granularities, and the lack of widely accepted interfaces and consequent limited connectivity between modules, can result in substantially underutilized Watts and FLOPS. To address these gaps, the HPC community needs a holistic stack for power and energy management and none currently exists. In our view, a holistic stack is one that is extensible enough to support the present and anticipated future needs of various different HPC centers, one that achieves best system performance and throughput through application-awareness, one that is designed to coordinate management at different granularities, and one that enables the seamless integration of software components from different developers and vendors. In this seminar, our goal is bring together experts from academia, research laboratories, and industry in order to take stock of existing approaches, design points and power management concepts and requirements at the various participant’s institutions, and to design concepts for a holistic power and energy management stack, which we refer to as the HPC PowerStack. Further, we hope to take steps toward defining the interfaces necessary for providing a complete prototype shared among many groups. The intention is to align development and research efforts across the community so that we may share development resources, avoid duplicating effort, agree on common interfaces and reap the rewards together as a community. The intended final outcome of this collaboration will be a holistic, flexible and extensible concept of a software stack ecosystem that allows us to combine product-grade open-source software components to enable runtime optimization of system power, energy, and performance.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

REopt: A Platform for Energy System Integration and Optimization

REopt is a techno-economic decision support model used to optimize energy systems for buildings, campuses, communities, and microgrids. The primary application of the model is for optimizing the integration and operation of behind-the-meter energy assets. This report provides an overview of the model, including its capabilities and typical applications; inputs and outputs; economic calculations; technology descriptions; and model parameters, variables, and equations. The model is highly flexible, and is continually evolving to meet the needs of each analysis. Therefore, this report is not an exhaustive description of all capabilities, but rather a summary of the core components of the model.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Vertical-Axis Wind Turbine Steady and Unsteady Aerodynamics for Curved Deforming Blades

Vertical-axis wind turbines’ simpler design and low center of gravity make them ideal for floating wind applications. However, efficient design optimization of floating systems requires fast and accurate models. Low-fidelity vertical-axis turbine aerodynamic models, including double multiple streamtube and actuator cylinder theory, were created during the 1980s. Commercial development of vertical-axis turbines all but ceased in the 1990s until around 2010 when interest resurged for floating applications. Despite the age of these models, the original assumptions (2-D, rigid, steady, straight bladed) have not been revisited in full. When the current low-fidelity formulations are applied to modern turbines in the unsteady domain, aerodynamic load errors nearing 50% are found, consistent with prior literature. However, a set of steady and unsteady modifications that remove the majority of error is identified, limiting it near 5%. This paper shows how to reformulate the steady models to allow for unsteady inputs including turbulence, deforming blades, and variable rotational speed. A new unsteady approximation that increases numerical speed by 5–10× is also presented. Combined, these modifications enable full-turbine unsteady simulations with accuracy comparable to higher-fidelity vortex methods, but over 5000× faster.

17 WIND ENERGY↗