Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “core optimization”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Computing x-ray absorption spectra from linear-response particles atop optimized holes

State specific orbital optimized density functional theory (OO-DFT) methods, such as restricted open-shell Kohn–Sham (ROKS), can attain semiquantitative accuracy for predicting x-ray absorption spectra of closed-shell molecules. OO-DFT methods, however, require that each state be individually optimized. In this Communication, we present an approach to generate an approximate core-excited state density for use with the ROKS energy ansatz, which is capable of giving reasonable accuracy without requiring state-specific optimization. Herein, this is achieved by fully optimizing the core-hole through the core-ionized state, followed by the use of electron-addition configuration interaction singles to obtain the particle level. This hybrid approach can be viewed as a DFT generalization of the static-exchange (STEX) method and can attain ~0.6 eV rms error for the K-edges of C–F through the use of local functionals, such as PBE and OLYP. This ROKS(STEX) approach can also be used to identify important transitions for full OO ROKS treatment and can thus help reduce the computational cost of obtaining OO-DFT quality spectra. ROKS(STEX), therefore, appears to be a useful technique for the efficient prediction of x-ray absorption spectra.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Design and Optimization of a 200-kW Medium-Frequency Transformer for Medium-Voltage SiC PV Inverters

This paper presents a design and optimization methodology for a 200-kW medium-frequency transformer (MFT) based on low-loss magnetic core (FINEMET FT-3TL). The proposed optimal design methodology consists of predesign, preliminary design, and optimal design. In the preliminary design, the parallel-concentric winding structure is selected to increase the current carrying capability and reduce the leakage inductance. Based on the parallel-concentric winding concept, a novel cooing and insulation structure with 3-D printed bobbins are proposed. The optimal designed MFT prototype achieves a power density higher than 19.23 kW/L. The electrical insulation system is tested at 12 kV ac peak voltage. In addition, the partial discharge (PD) test is conducted at 7.5 kV ac peak voltage to ensure the PD-free design. The high-frequency bipolar pulsewidth modulation voltage insulation (PD) test is the first time applied in MFT design and test process. Finally, the transformer is applied in a dual-active-bridge (DAB) converter with 200 kW rated power. The peak efficiency of the DAB converter is 99.53%, and the efficiency at 200 kW is 98.85%. The peak efficiency of MFT is 99.844%, and the efficiency at 200 kW is 99.842%.

42 ENGINEERING↗
DOE OSTI2015

Locality Aware Concurrent Start for Stencil Applications

Stencil computations are at the heart of many physical simulations used in scientific codes. Thus, there exists a plethora of optimization efforts for this family of computations. Among these techniques, tiling techniques that allow concurrent start have proven to be very efficient in providing better performance for these critical kernels. Nevertheless, with many core designs being the norm, these optimization techniques might not be able to fully exploit locality (both spatial and temporal) on multiple levels of the memory hierarchy without compromising parallelism. It is no longer true that the machine can be seen as a homogeneous collection of nodes with caches, main memory and an interconnect network. New architectural designs exhibit complex grouping of nodes, cores, threads, caches and memory connected by an ever evolving network-on-chip design. These new designs may benefit greatly from carefully crafted schedules and groupings that encourage parallel actors (i.e. threads, cores or nodes) to be aware of the computational history of other actors in close proximity. In this paper, we provide an efficient tiling technique that allows hierarchical concurrent start for memory hierarchy aware tile groups. Each execution schedule and tile shape exploit the available parallelism, load balance and locality present in the given applications. We demonstrate our technique on the Intel Xeon Phi architecture with selected and representative stencil kernels. We show improvement ranging from 5.58% to 31.17% over existing state-of-the-art techniques.

Locality Aware execution, jagged tiling↗
DOE OSTI2022

Concurrent Enhancement of Acetylene Uptake Capacity and Selectivity by Progressive Core Expansion and Extra–Framework Anions in Pore–Space–Partitioned Metal–Organic Frameworks

A multi-stage core-expansion method is proposed here as one component of the integrative binding-site/extender/core-expansion (BEC) strategy. The conceptual deconstruction of the partitioning ligand into three editable parts draws our focus onto progressive core expansion and allows the optimization of both acetylene uptake and selectivity. Herein the effectiveness of this strategy is shown through a family of eight cationic pore-partitioned materials containing three different partitioning ligands and various counter anions. The optimized structure, Co 3 -cpt-tph-Cl (Hcpt=4-(p-carboxyphenyl)-1,2,4-triazole, H-tph=(2,5,8-tri-(4-pyridyl)-1,3,4,6,7,9-hexaazaphenalene) with the largest surface area and highest C 2 H 2 uptake capacity (200 cm 3 /g at 298 K), also exhibits (desirably) the lowest CO 2 uptake and hence the highest C 2 H 2 /CO 2 selectivity. The successful boost in both C 2 H 2 capacity and IAST selectivity allows Co 3 -cpt-tph-Cl to rank among the best crystalline porous materials, ionic MOFs in particular, for C 2 H 2 uptake and C 2 H 2 /CO 2 experimental breakthrough separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Efficient implementation of the many-body Reactive Bond Order (REBO) potential on GPU

The second generation Reactive Bond Order (REBO) empirical potential is commonly used to accurately model a wide range hydrocarbon materials. It is also extensible to other atom types and interactions. REBO potential assumes complex multi-body interaction model, that is difficult to represent efficiently in the SIMD or SIMT programming model. Hence, despite its importance, no efficient GPGPU implementation has been developed for this potential. Here we present a detailed description of a highly efficient GPGPU implementation of molecular dynamics algorithm using REBO potential. The presented algorithm takes advantage of rarely used properties of the SIMT architecture of a modern GPU to solve difficult synchronizations issues that arise in computations of multi-body potential. Techniques developed for this problem may be also used to achieve efficient solutions of different problems. The performance of proposed algorithm is assessed using a range of model systems. It is compared to highly optimized CPU implementation (both single core and OpenMP) available in LAMMPS package. These experiments show up to 6x improvement in forces computation time using single processor of the NVIDIA Tesla K80 compared to high end 16-core Intel Xeon processor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Optoelectronic polymer memristors with dynamic control for power-efficient in-sensor edge computing

Abstract As the demand for edge platforms in artificial intelligence increases, including mobile devices and security applications, the surge in data influx into edge devices often triggers interference and suboptimal decision-making. There is a pressing need for solutions emphasizing low power consumption and cost-effectiveness. In-sensor computing systems employing memristors face challenges in optimizing energy efficiency and streamlining manufacturing due to the necessity for multiple physical processing components. Here, we introduce low-power organic optoelectronic memristors with synergistic optical and mV-level electrical tunable operation for a dynamic “control-on-demand” architecture. Integrating signal sensing, featuring, and processing within the same memristors enables the realization of each in-sensor analogue reservoir computing module, and minimizes circuit integration complexity. The system achieves 97.15% fingerprint recognition accuracy while maintaining a minimal reservoir size and ultra-low energy consumption. Furthermore, we leverage wafer-scale solution techniques and flexible substrates for optimal memristor fabrication. By centralizing core functionalities on the same in-sensor platform, we propose a resilient and adaptable framework for energy-efficient and economical edge computing.

Optics↗
DOE OSTI2014

Study on neutronic of very small Pb - Bi cooled no-onsite refueling nuclear power reactor (VSPINNOR)

A conceptual design study on Very Small Pb-Bi No-Onsite Refueling Cooled Nuclear Reactor (VSPINNOR) with Uranium nitride fuel using MCNPX program has been performed. In this design the reactor core is divided into three regions with different enrichment. At the center of the core is laid fuel without enrichment (internal blanket). While for the outer region using fuel enrichment variations. VSPINNOR fast reactor was operated for 10 years without refueling. Neutronic analysis shows optimized result of VSPINNOR has a core of 50 cm radius and 100 cm height with 300 MWth thermal power output at 60% fuel fraction that can be operated 18 years without refueling or fuel shuffling.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Density and temperature profiles after low-Z and high-Z shattered pellet injections on DIII-D

Abstract In this work we utilize the recently upgraded Thomson scattering diagnostic to resolve density and temperature plasma profiles after pure deuterium and mixed neon/deuterium shattered pellet injections (SPIs) on DIII-D. This allows us to study individual components of the staggered scheme proposed for disruption mitigation on ITER, consisting of a low-Z material SPI followed by a delayed high-Z SPI. Obtained spatio-temporal density profiles exhibit very different dynamics after dominantly neon and pure deuterium SPIs. The neon SPI causes a fast radiative plasma collapse in a few milliseconds and results in almost flat density profile once the impurity mixes with the plasma during and after the thermal quench (TQ). The deuterium SPI leads to a disruption delayed by ten and more milliseconds, but very limited core fueling can be observed before the disruption. Even during and after the TQ, the edge deuterium density significantly exceeds the core density. 1D transport modeling suggests that this poor core fueling can be explained by strong outward grad-B-induced drift of the injected deuterium. Preliminary simulations show that larger pellet shards and greater injected quantity can be used to improve the penetration of the low-Z material into the core. These results call for optimization and further evaluation of the staggered SPI on ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Redundantly Amplified Information Suppresses Quantum Correlations in Many-Body Systems

We establish bounds on quantum correlations in many-body systems. They reveal what sort of information about a quantum system can be simultaneously recorded in different parts of its environment. Specifically, independent agents who monitor environment fragments can eavesdrop only on amplified and redundantly disseminated—hence, effectively classical—information about the decoherence-resistant pointer observable. We also show that the emergence of classical objectivity is signaled by a distinctive scaling of the conditional mutual information, bypassing hard numerical optimizations. Our results validate the core idea of quantum Darwinism: objective classical reality does not need to be postulated and is not accidental, but rather a compelling emergent feature of quantum theory that otherwise—in the absence of decoherence and amplification—leads to “quantum weirdness.” In particular, a lack of consensus between agents that access environment fragments is bounded by the information deficit, a measure of the incompleteness of the information about the system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Irradiation tests of prototype self-powered gamma and neutron detectors

In the framework of the SCK.CEN-CEA Joint Instrumentation Laboratory, we are developing and optimizing a self-powered detector for selective in-core monitoring of the gamma field. Several prototypes with bismuth emitters were developed and tested in a pure gamma field (the PAGURE gamma irradiation facility at CEA) and in mixed neutron and gamma fields (in the OSIRIS reactor at CEA and in the BR2 reactor at SCK.CEN). Detailed MCNP modelling was performed to calculate the gamma and neutron sensitivities. Apart from a few failing prototypes, all detectors showed equilibrium signals proportional to the gamma field with a good long-term stability (under irradiation during several weeks). A tubular geometry design was finally selected as the most appropriate for in-core gamma detection, coupling a larger sensitivity with better response characteristics. In the same experiment in BR2 six prototype Self-Powered Neutron Detectors (SPNDs) with continuous sheaths (i.e. without any weld between the sensitive part and the cable) were extensively tested: two SPNDs with Co emitter, two with V emitter and two with Rh emitters, with varying geometries. All detector responses were verified to be proportional to the reactor power. The prompt and delayed response contributions were quantified. The signal contributions due to the impact of gamma rays were experimentally determined. The evolution of the signals was continuously followed during the full irradiation period. The signal-to-noise level was observed to be well below 1% in typical irradiation conditions. The absolute neutron and gamma responses for all SPNDs are consistent. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

SRNL 2017 LDRD Annual Report

Fiscal Year (FY) 2017 marked the twelfth year of Savannah River National Laboratory’s (SRNL’s) Laboratory Directed Research and Development (LDRD) program and the largest year to date. When the program began in FY06, just two years after SRNL becoming the DOE’s 17th national lab, it began with a modest authorized collection rate of just under 1.5%. It grew from there each year, reaching 4% in FY11. FY17 marked the first increase in the authorized collection rate since FY11, increasing from 4% to 5%. This increase highlights the value placed on this important program, which provides the discretionary funding needed to develop ideas for future programmatic growth in our key business areas of environmental stewardship, national security, nuclear materials management, and secure energy manufacturing, as well as develop and maintain our core competencies. The LDRD program leverages the unique capabilities of SRNL to yield foundational scientific research and development (R&D) essential to our core business areas, while aligning optimally and continuously with SRNL’s Strategic Plan and providing long-term benefits to DOE and the National Nuclear Security Administration (NNSA), other customers, and stakeholders. As can be seen in the “By the Numbers” summary, this program also plays an important role in sustaining staff excellence with high participation by students, post-docs, and early-career staff. Over 75% of the projects in FY17 included contributions from early-career or post-doctoral staff.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

2018 LDRD annual report

Fiscal Year (FY) 2018 marked the thirteenth year of Savannah River National Laboratory’s (SRNL’s) Laboratory Directed Research and Development (LDRD) program and the largest year to date. When the program began in FY06, just two years after SRNL becoming the DOE’s 17th national lab, it began with a modest authorized collection rate of just under 1.5%. It grew from there each year, reaching 5% in FY17. The authorized collection rate was maintained at 5% on FY18. The increase in collection rates experienced during the last years evidences the value placed on this important program, which provides the discretionary funding needed to develop ideas for future programmatic growth in our key business areas of environmental stewardship, national security, nuclear materials management, and secure energy manufacturing, as well as develop and maintain our core competencies. The LDRD program leverages the unique capabilities of SRNL to yield foundational scientific research and development (R&D) essential to our core business areas, while aligning optimally and continuously with SRNL’s Strategic Plan and providing long-term benefits to DOE and the National Nuclear Security Administration (NNSA), other customers, and stakeholders. As can be seen in the “By the Numbers” summary, this program also plays an important role in sustaining staff excellence with high participation by students, post-docs, and early-career staff. Over 85% of the projects in FY18 included contributions from early-career or post-doctoral staff.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Multi-Functional Distributed Fiber Sensors for Pipeline Monitoring and Methane Detections. Final Report

As an abundant and cheap fossil energy source, natural gas has become a significant energy supply to support the United States’ economy. However, the large-scale extraction and utilization of natural gas also impose significant challenges on methane leakage. This problem is exacerbated by aging gas utility delivery systems, including interstate high-pressure pipelines, storage, and transmission facilities. This project aims to develop a cost-effective fiber optical sensing method that can perform multi-parameter real-time measurements of natural gas pipelines across long interrogation distances up to 100 km with 1-meter spatial resolution. This sensing tool can evaluate overall pipeline efficiency and reduce methane emissions for mid-stream methane infrastructures. To accomplish this objective, research and development efforts funded by this project have resulted in the following accomplishments: This project successfully has developed new functional sensory polymer materials using Metal-Organic Frameworks (MOFs) that can be coated on optical fiber through the reel-to-reel coating process. Functional polymer-coated optical fibers can perform sensitive methane detection through evanescence wave interaction and strain-based measurements to achieve 1% detection sensitivities. The new sensors fibers support both distributed measurements and multiplexed fiber sensors array for multi-point measurements. This project developed and optimized a new multi-core optical fiber that supports simultaneous and distributed measurements of strain and temperatures with 1-meter spatial resolutions across up to 100-km interrogation distance. This new fiber, combined with sensory polymercoated fiber, could perform both distributed temperature and methane detections. This project developed a new artificial intelligence big data algorithm approach that can effectively analyze high-resolution data harnessed by distributed fiber sensors to protect natural gas pipelines against external threats and detect internal defects induced by corrosion. Working with our industry partner, this project developed new optical fibers that support fiber sensor fabrications through polymer coating after the fibers are drawn. These new fibers eliminate the need for direct sensor fabrication when the fiber is fabricated on a fiber draw tower, which drastically expands fiber sensors' applicability. This research project has significantly advanced the distributed fiber sensing technology. It will dramatically increase the applicability and adaptability of distributed fiber sensors for a wide array of applications in energy, sustainability, and environmental science, including structural health monitoring of natural gas pipelines, oil infrastructures, hydrogen facilities, and environmental monitoring of carbon storage sites, water supply systems, and others.

03 NATURAL GAS↗
DOE OSTI2021

FY2020 LDRD Annual Report

The Laboratory Directed Research and Development (LDRD) program funds scientific efforts to build upon the unique knowledge base of Savannah River National Laboratory (SRNL). The program yields foundational scientific research and development (R&D) essential to SRNL’s core business areas, while aligning optimally and continuously with SRNL’s Strategic Plan and providing long-term benefits to DOE and the National Nuclear Security Administration (NNSA), other customers, and stakeholders. While fiscal year (FY) 2020 presented unprecedented challenges due to the COVID-19 global pandemic, the SRNL research team continued to advance science and further technology through the support of the LDRD program.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Savannah River National Laboratory (FY2021 LDRD Annual Report)

Research efforts to build upon the unique knowledge base of the Savannah River National Laboratory (SRNL) are funded through the Laboratory Directed Research and Development (LDRD) Program. The program yields foundational scientific research and development (R&D) essential to SRNL’s core business areas, while aligning optimally and continuously with SRNL’s Strategic Plan to provide long-term benefits to the Department of Energy (DOE), the National Nuclear Security Administration (NNSA), and other customers and stakeholders.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Particle In Cell Scalable Application Resource (PICSAR) v2

PICSAR, for Particle-In-Cell Scalable Application Resource, is a high-performance Particle-in-Cell library developed in Fortran 90 and Python. This library was first developed to be coupled with WARP and provide efficient subroutines optimized for Many-Integrated Core (MIC) architectures such as the forthcoming system Cori Phase II that will be equipped with Intel Xeon Phi KNL processors. It is a compact self-contained proxy that adequately portrays the computational loads and dataflow of the more complex WARP code but can also be used by other PIC codes. PICSAR also contains a Fortran stand-alone Particle-In-Cell "mini-app" that includes the key functionalities of a PIC code. This stand-alone code is used for testing implementation performances and to do some benchmarks.

VINCENTI, HENRI↗
DOE OSTI2020

NREL's Capabilities in Organism Development and Fermentation Sciences Research and Development (R&D)

NREL is developing robust microbial strains and scalable fermentation technologies for converting biomass sugars to fuels and biochemicals, and one-carbon (C1) gaseous substrates (e.g., CO2, CO, CH4) to high-value products. Core capabilities include: (1) Fermentation optimization of aerobic, microaerophilic, and anaerobic cultivation processes of gas and traditional liquid fermentation R&D; (2) Gas mass transfer R&D and CFD modeling for improved reactor design and gas mixing (3) Metabolic engineering in CRISPR editing tools to improve titer, rates, and yields; (4) Probing and optimizing carbon, redox, and energy flux using transcriptomics and fluxomic techniques; and (5) Consolidated bioprocessing (CBP) using cellulose and hemicellulose directly to minimize pretreatment.

BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS,SYNTHETIC ↗
DOE OSTI2023

Method and apparatus for constructing informative outcomes to guide multi-policy decision making

In Multi-Policy Decision-Making (MPDM), many computationally-expensive forward simulations are performed in order to predict the performance of a set of candidate policies. In risk-aware formulations of MPDM, only the worst outcomes affect the decision making process, and efficiently finding these influential outcomes becomes the core challenge. Recently, stochastic gradient optimization algorithms, using a heuristic function, were shown to be significantly superior to random sampling. In this disclosure, it was shown that accurate gradients can be computed-even through a complex forward simulation—using approaches similar to those in dep networks. The proposed approach finds influential outcomes more reliably, and is faster than earlier methods, allowing one to evaluate more policies while simultaneously eliminating the need to design an easily-differentiable heuristic function.

Olson, Edwin↗