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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Verification of a Numerical Model of the Offshore Wind Turbine from the Alpha Ventus Wind Farm Within OC5 Phase III: Preprint

The main objective of the Offshore Code Comparison Collaboration Continuation, with Correlation (OC5) project, is validation of aero-hydro-servo-elastic simulation tools for offshore wind turbines (OWTs) through comparison of simulated results to the response data of physical systems. Phase III of the OC5 project analyzes the Senvion 5M wind turbine supported by the OWEC Quattropod from the alpha ventus offshore wind farm. This paper shows results of the verification of the OWT models (code-to-code comparison). A subsequent publication will focus on their validation (comparison of simulated results to measured physical system response data). Based on the available data, the participants of Phase III set up numerical models of the OWT in their simulation tools. It was necessary to verify and to tune these models. The verification and tuning were performed against an OWT model available at the University of Stuttgart - Stuttgart Wind Energy (SWE) and documentation provided by Senvion and OWEC Tower. A very good match was achieved between the results from the reference SWE model and models set up by OC5 Phase III participants.

17 WIND ENERGY↗
DOE OSTI2017

Trends of Alkane Activation on Doped Cobalt (II, III) Oxide from First Principles

The surface doping of a metal oxide can tune its catalytic performance, but it remains unclear how the tuning depends on the dopant type and the surface facet. In this report we study doped Co 3 O 4 (1 1 1) and (3 1 1) surface facets using first-principles density functional theory (DFT) to obtain general descriptors for oxygen reactivity (which include vacancy formation energy and hydrogen adsorption energy) and correlate them to ethane C-H activation energy as a measure of the catalytic performance. The periodic trends of the dopants are investigated for a total of 20 dopants, namely, the elements from K to Ge. We find strong linear correlations between the oxygen reactivity descriptors and the computed energy barriers. We also discover a strong surface facet sensitivity among certain dopants such that different surface orientations and sites lead to different or even the opposite dopant performance. This work provides a useful guide for dopant performance in ethane activation on the two very different Co 3 O 4 surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Performance Impact and Trade-Offs for Tuning Key Architectural Parameters on CPU+GPU Systems

In this work, we performed an initial design space exploration of an accelerated processing unit (APU)—a hybrid CPU+GPU architecture that integrates both compute units (CUs) and memory into a unified system. This integration aims to reduce data movement, enhance memory locality, and improve energy efficiency by enabling the CPU and GPU to share memory directly. This effort focused on the interplay of key design components—cache line size, the number of CUs, and main memory technology—and the trade-offs of each configuration were analyzed. This paper highlights the various configurations’ impact on memory accesses, data reuse, and power utilization. The results provide valuable insights that can be leveraged to optimize APU architectures for high-performance and energy-efficient computing and thus create a balanced architecture. This optimization can be achieved by adopting dynamic cache management, runtime CU scaling, and advanced memory integration, highlighting the potential of APUs to address critical challenges in compute, data movement, and memory power consumption.

Asifuzzaman, Kazi [ORNL] (ORCID:0000000240044791)↗
DOE OSTI2023

Gradient-Descent-Based Learning Gain for Backstepping Controller and Disturbance Observer of Nonlinear Systems

This paper proposes a gradient-descent-based learning (GL) gain for backstepping controller and disturbance observer (DOB) of nonlinear system. The proposed method consists of the GL gain update law, controller, and DOB. The GL gain update law is proposed to adapt the control gain and DOB gain according to the direction that minimizes the cost function. The mathematical analysis reveals that the GL gain always has a positive sign and upper bound. The controller is designed via a backstepping procedure to track the desired output with GL control gain. The DOB is designed to estimate the unknown external disturbance with the GL DOB gain. Because the control and DOB gains are simultaneously tuned to achieve improved performance, the time consumption for tuning can be reduced. In addition, the peaking phenomenon can be avoided initially by a small initial value of GL gains. The stability of the closed-loop system is guaranteed using the input-to-state stability property. The performance of the proposed method was validated via simulations and experiments using a DC motor.

42 ENGINEERING↗
DOE OSTI2025

Inertial Confinement Fusion Design Search Using Bayesian Optimization

Inertial confinement fusion (ICF) experiments rely on complex multi-physics simulation codes such as the Lawrence Livermore National Laboratory-developed HYDRA to guide design work. However, these simulations have several dozen tunable parameters and can be computationally expensive. This makes searching the parameter space challenging and time-consuming. Recently developed automated tools utilize Bayesian optimization to search these high-dimensional parameter spaces for optimal designs. The optimization tools run 2D integrated simulations in HYDRA to converge on a design that produces specified scalar or vector outputs. In this paper, we apply the Bayesian optimization tools to two common tuning scenarios. First, we tune simulation inputs to match measurements of a well-characterized experiment at the National Ignition Facility. This type of tuning is commonly performed to compensate for the use of simplified simulation settings (e.g. reduced resolution) or to account for missing physics in the simulations. Second, we search for an ICF simulation design that has a particular radiation drive profile. These optimizations replicate the kinds of tuning researchers routinely perform, but do so with significantly reduced manual effort. This approach demonstrates a powerful and efficient pathway toward autonomous, high-fidelity design optimization for future ICF experiments.

Bayesian optimization↗
DOE OSTI2015

Connecting Performance Analysis and Visualization to Advance Extreme Scale Computing

The characterization, modeling, analysis, and tuning of software performance has been a central topic in High Performance Computing (HPC) since its early beginnings. The overall goal is to make HPC software run faster on particular hardware, either through better scheduling, on-node resource utilization, or more efficient distributed communication.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Verifying the structure-property-performance relationship of Y6-based small molecule acceptors by alkoxy-side chain isomerization and conjugated skeleton asymmetry

Non-fullerene small molecule acceptors (NF-SMAs) such as Y6 derivatives were the current working horse for the top performing polymer solar cells (PSCs). For this reason, numerous chemical modifications have been explored for establishing structure–property-performance relationship for Y6-based NF-SMAs. In this work, we explored the isomerization on asymmetrical Y6 derivatives by varying the position of alkoxy side chain on the thiophene linkage between the core and one of the end groups of Y6. The isomers with differences in conformational restriction raised by noncovalent interactions as well as steric hindrance revealed distinctive behavior in crystallization and polymorphism, which led to a significant contrast in PSC performances. Here the X-TO1 molecule with alkoxy side chain facing the end group (outward) displayed preferred molecular configuration and polymorph, delivering power conversion efficiency (PCE) of 15.63%, while its isomer X-TO2 showed coexisted polymorphs significantly increased the charge recombination in the PSC devices led to a low PCE around 3%. This structure–property-performance relationship not only highlighted the elegancy of isomerization in tuning the photovoltaic performances but also identified polymorphism as one of the causes for impairing photovoltaic performances of PSCs.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Fluorinated Lewis Acidic Organoboron Tunes Polysulfide Complex Structure for High–Performance Lithium–Sulfur Batteries

Many challenges in lithium-sulfur (Li–S) batteries are associated with the radical change in lithium polysulfide (LPS) solubility during cycling, but chemical approaches to address such inconsistency are still lacking. Here, the use of a strong Lewis acidic fluorinated organoboron, tri(2,2,2-trifluoroethyl) borate (TFEB), is reported as a multi-functional mediator to simultaneously overcome multiple technical barriers in practical Li–S batteries. TFEB acts as an anion acceptor and forms strong molecular complexes with Lewis basic LPS. The TFEB-LPS complexes have consistent solubility across the full polysulfide spectrum and deliver several times improved better redox kinetics, unlocking a true redox catalytic mechanism that covers the majority of redox events in thick sulfur cathodes. As a result, Li–S batteries evaluated under practical conditions exhibit significantly improved discharge capacity, rate capability, and cycling stability with the addition of the TFEB additive. More importantly, TFEB also contributes to the stabilization of lithium anode in the presence of polysulfides by generating strong interfacial film. These attributes significantly improve the cycling stability of practical Li–S pouch cells, which are assembled with a unit energy density of 219 Wh kg –1 . Finally, the results provide new molecular insights on the design of unlocking solvation networks of practical Li–S systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Polymer Hole Transport Material Functional Group Tuning for Improved Perovskite Solar Cell Performance

As lead halide perovskites (LHPs) continue to achieve success as a light-harvesting material in perovskite solar cells (PSCs), exploring and understanding other materials in the device stack become increasingly important. Particularly, selection of suitable hole transport materials (HTMs) that demonstrate high performance and stability is imperative in the design of P-I-N PSCs. Presented here are a family of 12 structurally related polymers based on either fluorene or carbazole main chains with select aromatic side groups that introduce tunable properties for use in PSCs. How properties such as the highest occupied molecular orbital energy level, conductivity, glass-transition temperature, and wettability of the HTM affect the PSC performance is explored. Devices that incorporate the polymer HTMs perform well relative to PTAA in benchmark P-I-N PSC architectures while exhibiting similar or superior stability under accelerated aging studies. The relative synthetic simplicity and resultant performance of the HTMs in PSCs coupled with the ability to customize properties with different functional groups demonstrates the potential of this family of HTMs for a variety of LHP materials.

14 SOLAR ENERGY↗
DOE OSTI2023

Surface Lattice-Embedded Pt Single-Atom Catalyst on Ceria-Zirconia with Superior Catalytic Performance for Propane Oxidation

Tuning the metal–support interaction and coordination environment of single-atom catalysts can help achieve satisfactory catalytic performance for targeted reactions. Herein, via the facile control of calcination temperatures for Pt catalysts on pre-stabilized Ce 0.9 Zr 0.1 O 2 (CZO) support, Pt single atoms (Pt 1 ) with different strengths of Pt–CeO 2 interaction and coordination environment were successfully constructed. With the increase in calcination temperature from 350 to 750 °C, a stronger Pt–CeO 2 interaction and higher Pt-O-Ce coordination number were achieved due to the reaction between PtO x and surface Ce 3+ species as well as the migration of Pt 1 into the surface lattice of CZO. The Pt/CZO catalyst calcined at 750 °C (Pt/CZO-750) exhibited a surprisingly higher C 3 H 8 oxidation activity than that calcined at 550 °C (Pt/CZO-550). Here, through systematic characterizations and reaction mechanism study, it was revealed that the higher concentration of surface Ce 3+ species/oxygen vacancies and the stronger Pt–CeO 2 interaction on Pt/CZO-750 could better facilitate the activation of oxygen to oxidize C 3 H 8 into reactive carbonate/carboxyl species and further promote the transformation of these intermediates into gaseous CO 2 . The Pt/CZO-750 catalyst can be a potential candidate for the catalytic removal of hydrocarbons from vehicle exhaust.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Electrochemical tuning of capacitive response of graphene oxide

The increasing energy demands of modern society require a deep understanding of the properties of energy storage materials, as well as the tuning of their performance. We show that the capacitance of graphene oxide (GO) can be precisely tuned using a simple electrochemical reduction route. In situ resistance measurements, in combination with cyclic voltammetry measurements and Raman spectroscopy, have shown that upon reduction GO is irreversibly deoxygenated, which is further accompanied by structural ordering and an increase in electrical conductivity. The capacitance is maximized when the concentration of oxygen functional groups is properly balanced with the conductivity. Any further reduction and deoxygenation leads to a gradual loss of capacitance. The observed trend is independent of the preparation route and the exact chemical and structural properties of GO. It is proposed that an improvement in the capacitive properties of any GO can be achieved by optimization of its reduction conditions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Simplifying Performance Analysis of Large-scale Adaptive Scientific Applications

Performance analysis of parallel scientific codes is becoming increasingly difficult due to the rapidly growing complexity of applications and architectures. Existing tools fall short in providing intuitive views that facilitate the process of performance debugging and tuning. In this paper, we exploit a recent idea of projecting and visualizing performance data on the communication and hardware domain for faster, more intuitive analysis of applications. We leverage several performance analysis and visualization tools to showcase the discovery of scalability bottlenecks in a structured AMR library. Using novel techniques to project per-phase timing data, application data, and communication data on a communication graph, we identify a previously elusive scaling bottleneck in the library. We present solutions that mitigate this problem, resulting in 22% improvement in the performance for a 65,536-core run on an IBM Blue Gene/P system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Measuring and tuning energy efficiency on large scale high performance computing platforms.

Recognition of the importance of power in the field of High Performance Computing, whether it be as an obstacle, expense or design consideration, has never been greater and more pervasive. While research has been conducted on many related aspects, there is a stark absence of work focused on large scale High Performance Computing. Part of the reason is the lack of measurement capability currently available on small or large platforms. Typically, research is conducted using coarse methods of measurement such as inserting a power meter between the power source and the platform, or fine grained measurements using custom instrumented boards (with obvious limitations in scale). To collect the measurements necessary to analyze real scientific computing applications at large scale, an in-situ measurement capability must exist on a large scale capability class platform. In response to this challenge, we exploit the unique power measurement capabilities of the Cray XT architecture to gain an understanding of power use and the effects of tuning. We apply these capabilities at the operating system level by deterministically halting cores when idle. At the application level, we gain an understanding of the power requirements of a range of important DOE/NNSA production scientific computing applications running at large scale (thousands of nodes), while simultaneously collecting current and voltage measurements on the hosting nodes. We examine the effects of both CPU and network bandwidth tuning and demonstrate energy savings opportunities of up to 39% with little or no impact on run-time performance. Capturing scale effects in our experimental results was key. Our results provide strong evidence that next generation large-scale platforms should not only approach CPU frequency scaling differently, but could also benefit from the capability to tune other platform components, such as the network, to achieve energy efficient performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Automated Cache Performance Analysis And Optimization

While there is no lack of performance counter tools for coarse-grained measurement of cache activity, there is a critical lack of tools for relating data layout to cache behavior to application performance. Generally, any nontrivial optimizations are either not done at all, or are done ”by hand” requiring significant time and expertise. To the best of our knowledge no tool available to users measures the latency of memory reference instructions for particular addresses and makes this information available to users in an easy-to-use and intuitive way. In this project, we worked to enable the Open|SpeedShop performance analysis tool to gather memory reference latency information for specific instructions and memory addresses, and to gather and display this information in an easy-to-use and intuitive way to aid performance analysts in identifying problematic data structures in their codes. This tool was primarily designed for use in the supercomputer domain as well as grid, cluster, cloud-based parallel e-commerce, and engineering systems and middleware. Ultimately, we envision a tool to automate optimization of application cache layout and utilization in the Open|SpeedShop performance analysis tool. To commercialize this software, we worked to develop core capabilities for gathering enhanced memory usage performance data from applications and create and apply novel methods for automatic data structure layout optimizations, tailoring the overall approach to support existing supercomputer and cluster programming models and constraints. In this Phase I project, we focused on infrastructure necessary to gather performance data and present it in an intuitive way to users. With the advent of enhanced Precise Event-Based Sampling (PEBS) counters on recent Intel processor architectures and equivalent technology on AMD processors, we are now in a position to access memory reference information for particular addresses. Prior to the introduction of PEBS counters, cache behavior could only be measured reliably in the aggregate across tens or hundreds of thousands of instructions. With the newest iteration of PEBS technology, cache events can be tied to a tuple of instruction pointer, target address (for both loads and stores), memory hierarchy, and observed latency. With this information we can now begin asking questions regarding the efficiency of not only regions of code, but how these regions interact with particular data structures and how these interactions evolve over time. In the short term, this information will be vital for performance analysts understanding and optimizing the behavior of their codes for the memory hierarchy. In the future, we can begin to ask how data layouts might be changed to improve performance and, for a particular application, what the theoretical optimal performance might be. The overall benefit to be produced by this effort was a commercial quality easy-to- use and scalable performance tool that will allow both beginner and experienced parallel programmers to automatically tune their applications for optimal cache usage. Effective use of such a tool can literally save weeks of performance tuning effort. Easy to use. With the proposed innovations, finding and fixing memory performance issues would be more automated and hide most to all of the performance engineer expertise ”under the hood” of the Open|SpeedShop performance tool. One of the biggest public benefits from the proposed innovations is that it makes performance analysis more usable to a larger group of application developers. Intuitive reporting of results. The Open|SpeedShop performance analysis tool has a rich set of intuitive, yet detailed reports for presenting performance results to application developers. Our goal was to leverage this existing technology to present the results from our memory performance addition to Open|SpeedShop. Suitable for experts as well as novices. Application performance is getting more difficult to measure as the hardware platforms they run on become more complicated. This makes life difficult for the application developer, in that they need to know more about the hardware platform, including the memory system hierarchy, in order to understand the performance of their application. Some application developers are comfortable in that sceario, while others want to do their scientific research and not have to understand all the nuances in the hardware platform they are running their application on. Our proposed innovations were aimed to support both experts and novice performance analysts. Useful in many markets. The enhancement to Open|SpeedShop would appeal to a broader market space, as it will be useful in scientific, commercial, and cloud computing environments. Our goal was to use technology developed initially at the and Lawrence Livermore National Laboratory combined with the development and commercial software experience of the Argo Navis Technologies, LLC (ANT) to form a powerful combination to delivery these objectives.

97 MATHEMATICS AND COMPUTING↗