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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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Project Management Plan/Progress Report: UT/GTKS Training Program Development for Commercial Building Operators (Final Report)

Universidad del Turabo (UT), in a collaborative effort with Global Turn Key Services, Inc. (GTKS), proposed to develop a training program and a commercialization plan for the development of Commercial Building Operators (CBOs). The CBOs will operate energy efficient buildings to help maintain existing buildings up to their optimal energy performance level, and ensure that net-zero-energy buildings continuously operate at design specifications, thus helping achieve progress towards meeting BTP Strategic Goals of creating technologies and design approaches that enable net-zero-energy buildings at low incremental costs by 2025. The proposed objectives were then: (1) Develop a Commercial Building Operator (CBO) training program and accreditation that will in turn provide a certification to participants recognized by Accreditation Boards such as the North American Board of Certified Energy Practitioners (NABCEP) and Leadership in Energy & Environmental Designs (LEED). (2) Develop and implement a commercialization and sustainability plan that details marketing, deployment, financial characterization, job placement, and other goals required for long-term sustainability of the project after the funding period. (3) After program development and deployment, provide potential candidates with the knowledge and skill sets to obtain employment in the commercial building green energy (net-zero-energy building) job market. The developed CBO training program will focus on providing skills for participants, such as displaced and unemployed workers, to enter the commercial building green energy (net-zeroenergy building) job market. This course was designed to allow a participant with minimal to no experience in commercial building green technology to obtain the required skill sets to enter the job market in as little as 12 weeks of intensive multi-faceted learning. After completion of the course, the CBO staff concluded the participant will meet minimum established accreditation standards established by UT and will complete the contact hours required of training to apply to the Certification on Energy Management (CEM) offered by the Association of Energy Engineers (AEE). The CBO training program consists of a combination of theory (classroom), online & computer simulation, laboratory & hands on (onsite) training lessons. The training is addressed four basic learning elements: (1) Learn the Technology; (2) Practice Skills with hands-on the Energy Simulation Builder program; (3) Final Project and Presentation; and, (4) Accreditation and Certifications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Using ensembles and distillation to optimize the deployment of deep learning models for the classification of electronic cancer pathology reports

One of the goals of the Surveillance, Epidemiology, and End Results (SEER) program is to estimate incidence, prevalence, and mortality of all cancers. To that end, cancer registries across the country maintain a massive database of cancer pathology reports which contain rich information to understand cancer trends. However, these reports are stored in the form of unstructured text, and human annotators are required to read and extract relevant information. In this article, we show that existing deep learning models for automating information extraction from cancer pathology reports can be significantly improved by using ensemble model distillation. We found that by training multiple predictive models and transferring their knowledge to a single, low-resource model, we can reduce the number of highly confident wrong predictions. Our results show that our implemented methods could save 1000s of manual annotation hours.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Semi-polar GaN Materials Technology for High IQE Green LEDs

The goal of this NETL funded program was to improve the IQE in green (and longer wavelength) nitride- based LEDs structures by using semi-polar GaN planar orientations for InGaN multiple quantum well (MQW) growth. These semi-polar orientations have the advantage of significantly reducing the piezoelectric fields that distort the QW band structure and decrease electron-hole overlap. In addition, semipolar surfaces potentially provide a more open surface bonding environment for indium incorporation, thus enabling higher indium concentrations in the InGaN MQW. The goal of the proposed work was to select the optimal semi-polar orientation and explore wafer miscuts around this orientation that produced the highest quantum efficiency LEDs. At the end of this program we had hoped to have MQWs active regions at 540 nm with an IQE of 50% and an EQE of 40%, which would be approximately twice the estimated current state-of-the-art.

Koleske, Daniel D.↗
DOE OSTI2014

LOW-COST LED LUMINAIRE FOR GENERAL ILLUMINATION

During this two-year Solid-State Lighting (SSL) Manufacturing R&D project Cree developed novel light emitting diode (LED) technologies contributing to a cost-optimized, efficient LED troffer luminaire platform emitting at ~3500K correlated color temperature (CCT) at a color rendering index (CRI) of >90. To successfully achieve program goals, Cree used a comprehensive approach to address cost reduction of the various optical, thermal and electrical subsystems in the luminaire without impacting performance. These developments built on Cree’s high- brightness, low-cost LED platforms to design a novel LED component architecture that will enable low-cost troffer luminaire designs with high total system efficacy. The project scope included cost reductions to nearly all major troffer subsystems as well as assembly costs. For example, no thermal management components were included in the troffer, owing to the optimized distribution of compact low- to mid-power LEDs. It is estimated that a significant manufacturing cost savings will result relative to Cree’s conventional troffers at the start of the project. A chief project accomplishment was the successful development of a new compact, high-efficacy LED component geometry with a broad far-field intensity distribution and even color point vs. emission angle. After further optimization and testing for production, the Cree XQ series of LEDs resulted. XQ LEDs are currently utilized in Cree’s AR series troffers, and they are being considered for use in other platforms. The XQ lens geometry influenced the independent development of Cree’s XB-E and XB-G high-voltage LEDs, which also have a broad intensity distribution at high efficacy, and are finding wide implementation in Cree’s omnidirectional A-lamps.

Lowes, Ted↗
DOE OSTI2018

Final Technical Report for: A Unified Data-Driven Approach for Programming In Situ Analysis and Visualization

The placement and movement of data is becoming the key limiting factor on both performance and energy efficiency of high performance computations. As systems generate more data, it is becoming increasingly difficult to actually move that data elsewhere for post-processing, as the rate of improvements in supporting I/O infrastructure is not keeping pace. Together, these trends are creating a shift in how we think about exascale computations, from a viewpoint that focuses on FLOPS to one that focuses on data and data-centric operations as fundamental to the reasoning about, and optimization of, scientific workflows on extreme-scale architectures. The overarching goal of our effort was the study of a unified data-driven approach for programming applications and in situ analysis and visualization. Our work was to understand the interplay between data-centric programming model requirements at extreme-scale and the overall impact of those requirements on the design, capabilities, flexibility, and implementation details for both applications and the supporting in situ infrastructure. In this context, we made many improvements to the Legion programming system (one of the leading data-centric models today) and demonstrated in situ analyses on real application codes using these improvements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

WinPSSP : a revamp of the computer program PSSP and its performance solving the crystal structures of small organic compounds and solids of biological and pharmaceutical interest

The direct-space methods software Powder Structure Solution Program ( PSSP ) [Pagola & Stephens (2010). J. Appl. Cryst. 43 , 370–376] has been migrated to the Windows OS and the code has been optimized for fast runs. WinPSSP is a user-friendly graphical user interface that allows the input of preliminary crystal structure information, integrated intensities of the reflections and FWHM, the definition of structural parameters and a simulated annealing schedule, and the visualization of the calculated and experimental diffraction data overlaid for each individual solution. The solutions are reported as filename.cif files, which can be used to analyze packing motifs and chemical bonding, and to input the atomic coordinates into the Rietveld analysis software GSAS. WinPSSP performance in straightforward crystal structure determinations has been evaluated using 18 molecular solids with 6–20 degrees of freedom. The free-distribution program as well as multimedia tutorials can be accessed at http://users.uoi.gr/nkourkou/winpssp/.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

REopt Screenings Catalyze Development of Hundreds of Megawatts of Renewable Energy for Federal Agencies

The U.S. Department of Energy's (DOE's) Federal Energy Management Program (FEMP) offers project assistance to federal agencies, which often begins with a desktop screening to develop a prioritized portfolio of renewable energy project opportunities. FEMP uses the National Renewable Energy Laboratory's (NREL) REopt energy planning platform to quickly and efficiently screen potential renewable energy opportunities at a single site or across a range of sites. REopt helps organizations prioritize the most economically and technically viable projects for further study, and identifies the size and mix of technologies that meet the organization's goals at minimum cost, along with the optimal operating strategies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Design of the High Rigidity Spectrometer at FRIB

A High Rigidity Spectrometer (HRS) has been designed for experiments at the Facility for Rare-Isotope Beams (FRIB) at Michigan State University (MSU). The HRS will allow experiments to be performed with the most exotic neutron-rich isotopes at high beam energies (≳100 MeV/u). The HRS consists of an analysis beamline called the High-Transmission Beamline (HTBL) and the spectrometer proper called the Spectrometer Section. Here, the maximum magnetic rigidity of the HRS is 8 Tm, which corresponds to the rigidities at which rare-isotope beams are optimally produced at FRIB. The resolving power, angular acceptance, and momentum acceptance are set to match the anticipated scientific program. An ion-optical design developed for the HRS is described in detail, along with the specifications of the associated magnet and detector systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Multi-Attribute Subset Selection enables prediction of representative phenotypes across microbial populations

The interpretation of complex biological datasets requires the identification of representative variables that describe the data without critical information loss. This is particularly important in the analysis of large phenotypic datasets (phenomics). Here we introduce Multi-Attribute Subset Selection (MASS), an algorithm which separates a matrix of phenotypes (e.g., yield across microbial species and environmental conditions) into predictor and response sets of conditions. Using mixed integer linear programming, MASS expresses the response conditions as a linear combination of the predictor conditions, while simultaneously searching for the optimally descriptive set of predictors. We apply the algorithm to three microbial datasets and identify environmental conditions that predict phenotypes under other conditions, providing biologically interpretable axes for strain discrimination. MASS could be used to reduce the number of experiments needed to identify species or to map their metabolic capabilities. The generality of the algorithm allows addressing subset selection problems in areas beyond biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Study of CdTe/CdS solar cell at low power density for low-illumination applications

In this paper, we numerically investigate CdTe/CdS PV cell properties using a simulation program Solar Cell Capacitance Simulator in 1D (SCAPS-1D). A simple structure of CdTe PV cell has been optimized to study the effect of temperature, absorber thickness and work function at very low incident power. Objective of this research paper is to build an efficient and cost effective solar cell for portable electronic devices such as portable computers and cell phones that work at low incident power because most of such devices work at diffused and reflected sunlight. In this report, we simulated a simple CdTe PV cell at very low incident power, which gives good efficiency.

14 SOLAR ENERGY↗
DOE OSTI2021

Effect of Nozzle Curvature on Supersonic Gas Jets Used in Laser-Plasma Acceleration

Supersonic gas jets produced by converging-diverging (C-D) nozzles are commonly used as targets for laser-plasma acceleration (LPA) experiments. A major point of interest for these targets is the gas density at the region of interaction where the laser ionizes the gas plume to create a plasma, providing the acceleration structure. Tuning the density profiles at this interaction region is crucial to LPA optimization. A "flat-top" density profile is desired at this line of interaction to control laser propagation and high energy electron acceleration, while a short high-density profile is often preferred for acceleration of lower-energy tightly-focused laser-plasma interactions. A particular design parameter of interest is the curvature of the nozzle's diverging section. We examine three nozzle designs with different curvatures: the concave "bell", straight conical and convex "trumpet" nozzles. We demonstrate that, at mm-scale distances from the nozzle exit, the trumpet and straight nozzles, if optimized, produce "flat-top" density profiles whereas the bell nozzle creates focused regions of gas with higher densities. An optimization procedure for the trumpet nozzle is derived and compared to the straight nozzle optimization process. We find that the trumpet nozzle, by providing an extra parameter of control through its curvature, is more versatile for creating flat-top profiles and its optimization procedure is more refined compared to the straight nozzle and the straight nozzle optimization process. Furthermore, we present results for different nozzle designs from computational fluid dynamics (CFD) simulations performed with the program ANSYS Fluent and verify them experimentally using neutral density interferometry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

The Kokkos EcoSystem: Comprehensive Performance Portability For High Performance Computing

State of the art Engineering and Science codes have grown in complexity dramatically over the last two decades. As a consequence application teams have adopted more sophisticated development strategies, leveraging third party libraries, deploying comprehensive testing and using advanced debugging and profiling tools. In todays environment of diverse hardware platforms, these applications also desire performance portability - avoiding the need to duplicate work for various platforms - which makes it necessary that these tools and libraries also work across the various systems. The Kokkos EcoSystem provides that portable software stack. Based on the Kokkos Core Programming Model, the EcoSystem provides math libraries, interoperability capabilities with Python and Fortran, and Tools for analysing, debugging, and optimizing applications. In this paper we will provide an overview of the components, discuss some specific use cases, and highlight how co-designing these components enables a more developer friendly experience.

42 ENGINEERING↗
DOE OSTI2025

Physics-Informed Graph Neural Networks for Collaborative Dynamic Reconfiguration and Voltage Regulation in Unbalanced Distribution Systems

Network reconfiguration has long been employed as a strategic approach to minimize power distribution system losses and effectively regulate voltage levels. Tap-changing voltage regulators are also critical for controlling bus voltages, especially in accommodating the increasing integration of distributed energy resources (DERs) with intermittent outputs. This paper introduces novel methodologies to address the challenges of dynamic reconfiguration and optimal tap setting in unbalanced three-phase distribution systems. We propose an approximated mixed-integer quadratically constrained program (MIQCP) to model dynamic reconfiguration, along with a pioneering formulation for voltage regulator (VR) tap-setting based on Special Ordered Set type 1 (SOS1). To mitigate computational complexity, we propose a physics-informed spatial-temporal graph convolutional network (STGCN) with an integrated link classifier. The proposed approach enables efficient solution generation by fixing specific variables in the MIQCP instance and solving the simplified sub-MIP using an MIP solver. Numerical studies demonstrate the superior prediction accuracy of our STGCN model compared to baseline neural network models, resulting in reduced DER curtailment and voltage deviation with shorter computation time.

dynamic reconfiguration↗
DOE OSTI2014

TH-A-19A-07: The Effect of Particle Tracking Step Size Limit On Monte Carlo- Computed LET Spectrum of Therapeutic Proton Beams

Purpose: To investigate the effect of charged particle tracking step size limit in the determination of the LET spectrum of therapeutic proton beams using Monte Carlo simulations. Methods: The LET spectra at different depths in a water phantom from a 79.7 MeV spot-scanning proton beam were calculated using Geant4. Five different tracking step limits 0.5 mm, 0.1 mm, 0.05 mm, 0.01 mm and 1 μm were adopted. The field size was set to 10×10 cm{sup 2} on the isocenter plane. A 40×40×6 cm{sup 3} water phantom was modelled as the irradiation target. The voxel size was set to 1×1×0.5 mm{sup 3} to obtain high resolution results. The LET spectra were scored ranging from 0.01 keV/μm to 10{sup 4}keV/μm in the logarithm scale. In addition, the proton energy spectra at different depths were also scored. Results: The LET spectra calculated using different step size limits were compared at four depths along the Bragg curve. At any depths, the spread of the LET spectra increases with the decrease of step size limit. In the dose buildup region (z = 1.9 cm) and in the region proximal to the Bragg peak (z = 3.95 cm), the frequency mean LET does not vary with decreasing step size limit. At Bragg peak (z = 4.75 cm) and in the distal edge (z = 4.85 cm), frequency mean LET decreases with decreasing step size limit. The energy spectrum at any specified depths does not vary with the step size limit. Conclusion: The calculated LET has a spectral distribution rather than a single value at any depths along the Bragg curve and the spread of the computed spectrum depends on the tracking step limit. Incorporating the LET spectrum distribution into the robust IMPT optimization plan may provide more accurate biological dose distribution than using the dose- or fluence-averaged LET. NIH Program Project Grant P01CA021239.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

ALESQP: An Augmented Lagrangian Equality-Constrained SQP Method for Optimization with General Constraints

Here we present a new algorithm for infinite-dimensional optimization with general constraints, called ALESQP. In short, ALESQP is an augmented Lagrangian method that penalizes inequality constraints and solves equality-constrained nonlinear optimization subproblems at every iteration. The subproblems are solved using a matrix-free trust-region sequential quadratic programming (SQP) method that takes advantage of iterative, i.e., inexact linear solvers, and is suitable for large-scale applications. A key feature of ALESQP is a constraint decomposition strategy that allows it to exploit problem-specific variable scalings and inner products. We analyze convergence of ALESQP under different assumptions. We show that strong accumulation points are stationary. Consequently, in finite dimensions ALESQP converges to a stationary point. In infinite dimensions we establish that weak accumulation points are feasible in many practical situations. Under additional assumptions we show that weak accumulation points are stationary. We present several infinite-dimensional examples where ALESQP shows remarkable discretization-independent performance in all of its iterative components, requiring a modest number of iterations to meet constraint tolerances at the level of machine precision. Also, we demonstrate a fully matrix-free solution of an infinite-dimensional problem with nonlinear inequality constraints.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Performance Portability of HPC Discovery Science Software: Fusion Energy Turbulence Simulations at Extreme Scale

As HPC R&D moves forward on a variety of “path to exascale” architectures today, an associated objective is to demonstrate performance portability of discovery-science-capable software. Important application domains, such as Magnetic Fusion Energy (MFE), have improved modelling of increasingly complex physical systems -- especially with respect to reducing “time-to-solution” as well as “energy to solution.” The emergence of new insights on confinement scaling in MFE systems has been aided significantly by efficient software capable of harnessing powerful supercomputers to carry out simulations with unprecedented resolution and temporal duration to address increasing problem sizes. Specifically, highly scalable particle-in-cell (PIC) programing methodology is used in this paper to demonstrate how modern scientific applications can achieve efficient architecture-dependent optimizations of performance scaling and code portability for path-to-exascale platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Distribution System V1G PEV Charging Impacts Report

Plug-in Electric Vehicles (PEVs) are a clean form of transportation that will require a new control paradigm between the energy supply and the transportation sectors as PEV adoption continues to grow. Meeting the projected PEV energy demands will require implementing PEV / grid integration methods beyond charging PEVs at incentivized times. MATLAB was used to simulate the daily vehicle trip demands and charging processes of hundreds of PEVs. The National Household Travel Survey (NHTS) data was used as the source of vehicle travel data, and EV Project provided measured PEV charging data to calibrate the PEV population models. GridLAB-D analyses used a prototypical feeder and PEV population models to evaluate residential PEV V1G (unidirectional) charging in multiple locations, V1G PEV distribution feeder impacts, Time-Of-Use (TOU) rate effects on PEV charging, and charging control methods. The key findings were: optimized charging using California TOU rates could result in savings of over $20 per month for non-TOU program participants; non-TOU participants consume 30-40% of PEV charging energy; about 50% of PEV drivers have their transportation fuel bill reduced by 50 dollars per month; 6.6kW charging will cause distribution transformer power limits to be exceeded on prototypical feeders if the household PEV adoption rate reaches 0.75 PEVs per home; distribution feeder loading is proportional to PEV charging rate; a method was devised to remotely identify when residential transformer overloads occur using changes in PEV charging rate; and the low-cost TOU period is composed of a distribution of PEVs needing small, medium and larger energy needs that can be more effectively shifted as groups to mitigate the TOU peak power and enable a higher PEV adoption rate per household without overloading distribution transformers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Hydrogen Diffusivity Measurements of YH 1.87 Moderator Material with Incoherent Quasielastic Neutron Scattering

Yttrium hydride is an optimal choice of moderator material for thermal neutron spectrum reactors requiring small core volumes. The Transformation Challenge Reactor (TCR) program at Oak Ridge National Laboratory (ORNL) aims to develop an additively manufactured microreactor core by leveraging recent advances in materials, manufacturing, data analytics, and high-fidelity modeling and simulation. Yttrium hydride was selected as the moderator material for TCR due to its high moderating power, which enables the spatially efficient reactor design and thermal stability that is superior when compared with zirconium hydride. Hydrogen desorption from yttrium hydride is expected at elevated temperatures, posing safety and performance concerns. As a lifetime component in advanced reactors, appropriate strategies to mitigate hydrogen release from yttrium hydride over long-term reactor operation are required. Understanding hydrogen mobility in yttrium hydride provides the scientific basis for developing a hydrogen barrier for hydride moderator and predicting the hydrogen redistribution within the material during various operational conditions. This study investigated the hydrogen motion in YH 1.87 as a function of temperature ranging from 200 to 1,173 K using incoherent quasielastic neutron scattering (IQNS) at the Spallation Neutron Source (SNS). The results are presented and discussed in terms of hydrogen self-diffusion coefficients, activation energy for translational hydrogen motion, and hydrogen jump distances. Based on the IQNS data, YH 1.87 is found to be stable at high temperatures with no translational H motion below 1,023 K within the IQNS detection limits. In the temperature range of 1,073–1,173 K, hydrogen diffusivity in YH 1.87 is $D = 4.57 X 10^{⁻3} [m^2/s] exp (⁻\frac{1.73[eV]}{RT}$). The hydrogen concentration’s dependence on hydrogen diffusivity is also discussed in this report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗