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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 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Progress Towards Accelerating the Unified Model on Hybrid Multi-Core Systems

The cloud microphysics scheme, CASIM, and the radiation scheme, SOCRATES, are two computationally intensive parts within the Met Office's Unified Model (UM). This study enables CASIM and SOCRATES to use accelerated multi-core systems for optimal computational performance of the UM. Using profiling to guide our efforts, we refactored the code for optimal threading and kernel arrangement and implemented OpenACC directives manually or through the CLAW source-to-source translator. Initial porting results achieved 10.02x and 9.25x speedup in CASIM and SOCRATES respectively on 1 GPU compared with 1 CPU core. A granular performance analysis of the strategy and bottlenecks are discussed. These improvements will enable UM to run on heterogeneous computers and a path forward for further improvements is provided.

Zhang, Wei↗
DOE OSTI2017

Molecular weight and uniformity define the mechanical performance of lignin-based carbon fiber

Lignin-based carbon fiber represents a renewable and low-cost alternative to petroleum-based carbon fiber. However, the poor mechanical performance of current lignin carbon fiber hinders its application. We hypothesized that the lower optimal mechanical performance is caused by the inherent heterogeneity of lignin. It is still unknown how the molecular weights (MWs) and lignin uniformity will impact the performance of lignin carbon fiber. We thereby addressed this hypothesis by fractionating lignin into fractions with different MWs and polydispersity indices (PDIs). An enzyme–mediator-based method and a dialysis method were developed to derive lignin fractions with increased MW and decreased PDI. Lignin fractions were electro-spun into fibers after blending with polyacrylonitrile (PAN) at 1 : 1 (w/w) ratio. The fractionation in general improved the spinnability of lignin to allow us to obtain finer lignin-based carbon fibers. The elastic modulus of lignin carbon fibers, as measured by nanoindentation, was increased as the lignin MW increased and as PDI decreased. The scatter plot and linear regression revealed very good correlation between the elastic modulus and PDI, as well as certain correlation between the elastic modulus and MW. XRD and Raman spectroscopy revealed that the crystallite size and the content of the pre-graphitic turbostratic carbon increased with higher lignin MW and lower PDI, revealing the mechanism of the improvement in carbon fiber mechanical performance. Finally, this study elucidated the impacts of lignin MW and uniformity on the mechanical properties of carbon fiber, and could thus guide the development of lignin processing technologies for quality lignin-based carbon fiber.

09 BIOMASS FUELS↗
DOE OSTI2019

Compressed Optimization of Device Architectures for Semiconductor Quantum Devices

Recent advances in nanotechnology have enabled researchers to manipulate small collections of quantum-mechanical objects with unprecedented accuracy. In semiconductor quantum-dot qubits, this manipulation requires controlling the dot orbital energies, the tunnel couplings, and the electron occupations. These properties all depend on the voltages placed on the metallic electrodes that define the device, the positions of which are fixed once the device is fabricated. While there has been much success with small numbers of dots, as the number of dots grows, it will be increasingly useful to control these systems with as few electrode voltage changes as possible. Here, we introduce a protocol, which we call the "compressed optimization of device architectures" (CODA), in order both to efficiently identify sparse sets of voltage changes that control quantum systems and to introduce a metric that can be used to compare device designs. As an example of the former, we apply this method to simulated devices with up to 100 quantum dots and show that CODA automatically tunes devices more efficiently than other common nonlinear optimizers. To demonstrate the latter, we determine the optimal lateral scale for a triple quantum dot, yielding a simulated device that can be tuned with small voltage changes on a limited number of electrodes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Collecting data in the home laboratory: evolution of X-ray sources, detectors and working practices

Recent developments in X-ray crystallographic hardware related to structural biology research are presented and discussed. While the majority of macromolecular X-ray data are currently collected using highly efficient beamlines at an ever-increasing number of synchrotrons, there is still a need for high-performance reliable systems for in-house experiments. In addition to crystal screening and optimization of data-collection parameters before a synchrotron trip, the home system allows the collection of data as soon as the crystals are produced to obtain the solution of novel structures, especially by the molecular-replacement method, and is invaluable in achieving the quick turnover that is often required for ligand-binding studies in the pharmaceutical industry. There has been a continuous evolution of X-ray sources, detectors and software developed for in-house use in recent years and a diverse range of tools for structural biology laboratories are available. An overview of the main directions of these developments and examples of specific solutions available to the macromolecular crystallography community are presented in this paper, showing that data collection ‘at home’ is still an attractive proposition complementing the use of synchrotron beamlines.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Advanced Performance Modeling with Combined Passive and Active Monitoring

To improve the efficiency of resource utilization and scheduling of scientific data transfers on high-speed networks, the "Advanced Performance Modeling with combined passive and active monitoring" (APM) project investigates and models a general-purpose, reusable and expandable network performance estimation framework. The predictive estimation model and the framework will be helpful in optimizing the performance and utilization of networks as well as sharing resources with predictable performance for scientific collaborations, especially in data intensive applications. Our prediction model utilizes historical network performance information from various network activity logs as well as live streaming measurements from network peering devices. Historical network performance information is used without putting extra load on the resources by active measurement collection. Performance measurements collected by active probing is used judiciously for improving the accuracy of predictions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Economically Viable Intermediate to Long Duration Hydrogen Energy Storage Solutions for Fossil Fueled Assets

This report was prepared as an account of work sponsored by the Office of Fossil Energy and Carbon Management of U.S. Department of Energy under Funding Opportunity Announcement Number DE-FOA-0002332 “Energy Storage for Fossil Power Generation”. The work aimed to explore and advance an innovative hydrogen energy storage system – the synergistically integrated hydrogen energy storage system (SIHES) – that has the following characteristics: • Compatible with existing or new coal and gas fuel electricity generation units, • best suited for intermediate to long duration energy storage, from 12 hours to weeks even months, and • capable of storing energy at the utility scale – hundreds of MWh to GWh energy storage with power output level in tens to hundreds of MW. Preliminary front-end engineering design (Pre-FEED) studies was carried out to develop and refine a site-specific SIHES as peaking power generation units (so named as HyPeaker) as the first market entry point, to demonstrate both the technical feasibility and the economic viability to integrate the HyPeaker “within the fence” of a fossil power plant. This specific site was TVA’s Johnsonville Combustion Turbine Plant. The HyPeaker was designed and engineered to integrate with a 60MW aeroderivative gas turbine unit already available at TVA’s Johnsonville site. This site-specific HyPeaker consists of an alkaline electrolyzer to produce hydrogen from CO 2 free electricity sources, an innovative low-cost high-pressure hydrogen storage system (Big-Ton) and the aero gas turbine to generate electricity using blend of hydrogen and natural gas. A holistic system level technoeconomic analysis tool specific to HyPeaker was developed to optimize the engineering design of the Johnsonville site-specific HyPeaker for cost and performance. The optimal design and specification of the Johnsonville site-specific HyPeaker are the following: • Alkaline electrolyzer: 3MW • Big-Ton storage vessel: 11,000kg H 2 at 3000psi. • 4-stage diaphragm hydrogen compressor: 55kg-H 2 /hr from 150psi to 3000psi. The HyPeaker is designed to provide sufficient hydrogen for 90% continuous operation of the HyPeaker. All major components have design life of 30 years. The capex of HyPeaker is estimated at $\$$7.1M. This included $\$$1.5M for the electrolyzer, $\$$5.6M for the storage vessel and compressor. The cost of aero gas turbine was included as it is already available at the site. Key findings are: • HyPeaker can be designed, manufactured, installed and integrated with the fossil power plants, with sub-systems and components commercially available on the market today, even when it is scaled up to an order of magnitude larger than the one at the Johnsonville site. HyPeaker is a technologically viable solution to cover a wide range of energy storage duration needs, from daily peaking operation to seasonal shifting for fossil fueled assets. • The cost advantage of SCCV based Big-Ton H 2 storage vessel made it possible to “oversize” the H 2 storage subsystem to achieve overall system level cost optimization. The benefits are two-fold. First, it allows to significantly reduce the capacity and cost of electrolyzer by spreading H 2 production over a much longer period of time when the fuel cost for electricity production is low. Second, it allows to balance the hydrogen production and usage shift over weeks to months to meet the peak demands. As such, the capital cost of HyPeaker system using the Big-Ton was less than half of the cost of a system with today’s steel tube based H 2 storage system. The HyPeaker has even better cost advantage Li-ion battery based energy storage system. The estimated capital cost of Li-Ion battery system would be at $\$$38M, under the same projected 20-year electricity generation profile of the Johnsonville site. This is over 5 times more expensive than the HyPeaker system. • Since industry scale energy storage systems do not have 100% energy conversion and storage efficiency, energy storage systems using fossil fuel generated electricity would increase the CO 2 emission. This is particularly the case for HyPeaker due to its low round trip efficiency. Therefore, a more sensible solution would be to the excessive or curtailed electricity from CO 2 emission free sources such as solar farms, wind farms or nuclear power plants, to produce hydrogen, and integrate them with the HyPeaker. Electricity from TVA’s nuclear power plants was used for the Johnsonville HyPeaker. • The economic viability of HyPeaker is expected to be further improved when global supply chains are taken into consideration. For the same Johnsonville site specific HyPeaker, the capex would be reduced to ~$\$$3.6M from ~$\$$7.1M, and the added LCOE is reduced to ~$\$$85/MWh. With the bipartisan Infrastructure Investment and Jobs Act, the cost of domestically produced HyPeaker sub-systems would be at the level of today’s global suppliers. Since the peaking units generally operate at peak usage period, thereby demanding higher price, the projected $\$$85/MWh LCOE would be within the realm of financial viability for utility operators.

08 HYDROGEN↗
NASA NTRS1972

Unmanned planetary spacecraft chemical rocket propulsion.

Review of some chemical propulsion technology advances suitable for future unmanned spacecraft applications. Discussed system varieties include liquid space-storable propulsion systems, advanced liquid monopropellant systems, liquid systems for rendezvous and landing applications, and low-thrust high-performance solid-propellant systems, as well as hybrid space-storable systems. To optimize the performance and operational characteristics of an unmanned interplanetary spacecraft for a particular mission, and to achieve high cost effectiveness of the entire system, it is shown to be essential that the type of spacecraft propulsion system to be used matches, as closely as possible the various requirements and constraints. The systems discussed are deemed to be the most promising candidates for some of the anticipated interplanetary missions.

Burlage, H., Jr.↗
NASA NTRS1983

ADS-1 - A new general-purpose optimization program

Today, numerous programs are available which may be coupled with finite element analysis or other analysis techniques to perform the optimization function in the solution of structural synthesis problems. However, most of these codes include only one or two algorithms and many have not been tested on problems of significant size and complexity. There is, therefore, a need for a reliable, general-purpose, publicly available code, containing a variety of modern algorithms for use in structural synthesis as well as general engineering design. The ADS-1 program (Automated Design Synthesis: Version 1) was written in response to this need. The present investigation has the objective to present the capabilities of the ADS program and to demonstrate its application to structural synthesis. The ADS program solves the general nonlinear constrained optimization problem in the standard form. At each level of the optimization process, several options are available.

Vanderplaats, G. N.↗
NASA NTRS1993

A comparative evaluation plan for the Maintenance, Inventory, and Logistics Planning (MILP) System Human-Computer Interface (HCI)

The primary goal of this project was to develop a tailored and effective approach to the design and evaluation of the human-computer interface (HCI) to the Maintenance, Inventory and Logistics Planning (MILP) System in support of the Mission Operations Directorate (MOD). An additional task that was undertaken was to assist in the review of Ground Displays for Space Station Freedom (SSF) by attending the Ground Displays Interface Group (GDIG), and commenting on the preliminary design for these displays. Based upon data gathered over the 10 week period, this project has hypothesized that the proper HCI concept for navigating through maintenance databases for large space vehicles is one based upon a spatial, direct manipulation approach. This dialogue style can be then coupled with a traditional text-based DBMS, after the user has determined the general nature and location of the information needed. This conclusion is in contrast with the currently planned HCI for MILP which uses a traditional form-fill-in dialogue style for all data access and retrieval. In order to resolve this difference in HCI and dialogue styles, it is recommended that comparative evaluation be performed which combines the use of both subjective and objective metrics to determine the optimal (performance-wise) and preferred approach for end users. The proposed plan has been outlined in the previous paragraphs and is available in its entirety in the Technical Report associated with this project. Further, it is suggested that several of the more useful features of the Maintenance Operations Management System (MOMS), especially those developed by the end-users, be incorporated into MILP to save development time and money.

Overmyer, Scott P.↗
NASA NTRS2004

Structured-groove phase gratings for control and optimization of the spectral efficiency

Phase gratings are used as dispersers in a variety of imaging spectroscopic instruments. However, conventional phase gratings provide limited spectral range and flexibility to fully optimize instrument performance for challenging applications. Presented here is a new design method that tailors and optimizes the spectral efficiency by introducing an arbitrary structure into the grating groove profile.

diffraction gratings↗
NASA NTRS2008

Vertical Isolation for Photodiodes in CMOS Imagers

In a proposed improvement in complementary metal oxide/semi conduct - or (CMOS) image detectors, two additional implants in each pixel would effect vertical isolation between the metal oxide/semiconductor field-effect transistors (MOSFETs) and the photodiode of the pixel. This improvement is expected to enable separate optimization of the designs of the photodiode and the MOSFETs so as to optimize their performances independently of each other. The purpose to be served by enabling this separate optimization is to eliminate or vastly reduce diffusion cross-talk, thereby increasing sensitivity, effective spatial resolution, and color fidelity while reducing noise.

Pain, Bedabrata↗
NASA NTRS2014

Supersonic Wing Optimization Using SpaRibs

This research investigates the advantages of using curvilinear spars and ribs, termed SpaRibs, to design a supersonic aircraft wing-box in comparison to the use of classic design concepts that employ straight spars and ribs. The objective is to achieve a more efficient load-bearing mechanism and to passively control the deformation of the structure under the flight loads. Moreover, the use of SpaRibs broadens the design space and allows for natural frequencies and natural mode shape tailoring. The SpaRibs concept is implemented in a new optimization MATLAB-based framework referred to as EBF3SSWingOpt. This optimization scheme performs both the sizing and the shaping of the internal structural elements, connecting the optimizer with the analysis software. The shape of the SpaRibs is parametrically defined using the so called Linked Shape method. Each set of SpaRibs is placed in a one by one square domain of the natural space. The set of curves is subsequently transformed in the physical space for creating the wing structure geometry layout. The shape of each curve of each set is unique; however, mathematical relations link the curvature in an effort to reduce the number of design variables. The internal structure of a High Speed Commercial Transport aircraft concept developed by Boeing is optimized subjected to stress, subsonic flutter and supersonic flutter constraints. The results show that the use of the SpaRibs allows for the reduction of the aircraft's primary structure weight without violating the constraints. A weight reduction of about 15 percent is observed.

Locatelli, David↗
NASA NTRS2018

Optimization of Elastodynamic Finite Integration Technique on Intel Xeon Phi Knights Landing Processors

This work describes the development and optimization of an implementation of an isotropic elastodynamic finite integration technique (EFIT) code for parallelized computation on Intel Knights Landing (KNL) hardware. EFIT is a numerical approach resulting in standard staggered-grid finite difference equations for the elastodynamic equations of motion to simulate bulk waves is solids. The computationally efficient simulation of elastodynamic wave propagation and interactions in aerospace materials is of high-interest in the fields of nondestructive evaluation (NDE) and structural health monitoring (SHM). Ultrasonic inspection uses an ultrasonic signal, generated at the surface of the material/structure via use of a piezoelectric transducer, to propagate sound waves into the material where it interacts with any existing defects, as well as with structural boundaries and any material inhomogeneity. Reflections from defects and boundaries are then measured by a transducer. Realistic ultrasound simulation tools can significantly aid the development and optimization of inspection techniques and can assist in the interpretation of experimental data. The optimization of an elastodynamics simulation code for the KNL Many Integrated Core processor was performed. The optimization focused on data locality and vectorization. Results show that tiling of the data to exploit the cache behavior and allow for significant utilization of the KNL hardware. The MPI implementation allows for a scalable implementation enabling large problems to be simulated. The model results were validated against theoretical dispersion curves to within 2% of the group velocity, and within 0.5% of the phase velocity of the A0 mode. Aggressive use of tiling, threading, and vectorization techniques allowed for dramatically improved time to solution.

William C. Schneck↗
DOE OSTI2020

Engine Combustion System Optimization Using Computational Fluid Dynamics and Machine Learning: A Methodological Approach

Gasoline compression ignition (GCI) engines are considered an attractive alternative to traditional spark-ignition and diesel engines. Here, a Machine Learning-Grid Gradient Ascent (ML-GGA) approach was developed to optimize the performance of internal combustion engines. ML offers a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. The developed ML-GGA model was compared with a recently developed Machine Learning-Genetic Algorithm (ML-GA). Detailed investigations of optimization solver parameters and variable limit extension were performed in the present ML-GGA model to improve the accuracy and robustness of the optimization process. Detailed descriptions of the different procedures, optimization tools, and criteria that must be followed for a successful output are provided here. The developed ML-GGA approach was used to optimize the operating conditions (case 1) and the piston bowl design (case 2) of a heavy-duty diesel engine running on a gasoline fuel with a research octane number (RON) of 80. The ML-GGA approach yielded >2% improvements in the merit function, compared with the optimum obtained from a thorough computational fluid dynamics (CFD) guided system optimization. The predictions from the ML-GGA approach were validated with engine CFD simulations. This study demonstrates the potential of ML-GGA to significantly reduce the time needed for optimization problems, without loss in accuracy compared with traditional approaches.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2019

Surrogate Modeling and Optimization of a Combustor with an Interdigitated Flushwall Injector

Design and Analysis of Computer Experiments (DACE) methods are applied and used to perform surrogate modeling and optimization of a simplified combustor flowpath with an interdigitated flushwall injector. The objectives of the optimization are the thrust potential and combustion efficiency, which are evaluated across a range of flight Mach numbers, duct heights, spanwise spacings, and injection angles. The focus of this work is to highlight the application of a sequential learning approach, in order to learn about the responses of the objective functions over the design space and to identify local regions of interest for further analysis. This approach is contrasted to a previous effort where only a single sampling set was used to fit surrogate models and perform optimization. The optimal solutions resulting from the previous and present approaches are different, due to surrogate model-guided local refinement of the design space allowed by the sequential learning method. The values of the global error estimates between the previous and present approaches are comparable, but the sequential method proved more computationally cost-effective. Further refinement in the optimal regions might be needed to improve predictive capability of surrogate models and to obtain the optimal solutions sets.

Rajiv R Shenoy↗
DOE OSTI2020

ENGINE COMBUSTION SYSTEM OPTIMIZATION USING CFD AND MACHINE LEARNING: A METHODOLOGICAL APPROACH

Gasoline compression ignition (GCI) engines are considered an attractive alternative to traditional spark-ignition and diesel engines. In this work, a Machine Learning-Grid Gradient Algorithm (ML-GGA) approach was developed to optimize the performance of internal combustion engines. Machine learning (ML) offers a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. The developed ML-GGA model was compared with a recently developed Machine learning Genetic Algorithm (ML-GA). Detailed investigations of optimization solver parameters and variables limits extension were performed in the present ML-GGA model to improve the accuracy and robustness of the optimization process. Detailed descriptions of the different procedures, optimization tools and criteria that must be followed for a successful output are provided here. The developed ML-GGA approach was used to optimize the operating conditions (case 1) and the piston bowl design (case 2) of a heavy-duty diesel engine running on a gasoline fuel with a Research Octane Number (RON) of 80. The ML-GGA approach yielded > 2% improvements in the merit function, compared to the optimum obtained from a thorough computational fluid dynamics (CFD) guided system optimization. The predictions from the ML-GGA approach were validated with engine CFD simulations. This study demonstrates the potential of ML-GGA to significantly reduce the time needed for optimization problems, without loss in accuracy compared to traditional approaches.

engine optimization↗
DOE OSTI2024

Riemannian Optimization Applied to AC Optimal Power Flow: Preprint

The nonlinear, nonconvex AC optimal power flow problem is of growing importance as the nature of the power grid evolves. This problem can be difficult to solve for interior point methods. However, the advent of optimization algorithms over smooth Riemannian manifolds presents an alternative approach. The nonlinear, nonconvex constraints in the AC power flow problem form an embedded submanifold of Euclidean space. In this paper, the authors explore the performance of Riemannian optimization algorithms for the ACOPF problem where the optimization is performed directly on the AC power flow manifold. They demonstrate that these are viable computational alternatives to interior point methods. This is done by using Julia and the packages PowerModels.jl and Manopt.jl.

manifold optimization↗