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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

A Framework for Daylighting Optimization in Whole Buildings with OpenStudio

We present a toolkit and workflow for leveraging the OpenStudio (Guglielmetti et al. 2010) platform to perform daylighting analysis and optimization in a whole building energy modeling (BEM) context. We have re-implemented OpenStudio's integrated Radiance and EnergyPlus functionality as an OpenStudio Measure. The OpenStudio Radiance Measure works within the OpenStudio Application and Parametric Analysis Tool, as well as the OpenStudio Server large scale analysis framework, allowing a rigorous daylighting simulation to be performed on a single building model or potentially an entire population of programmatically generated models. The Radiance simulation results can automatically inform the broader building energy model, and provide dynamic daylight metrics as a basis for decision. Through introduction and example, this paper illustrates the utility of the OpenStudio building energy modeling platform to leverage existing simulation tools for integrated building energy performance simulation, daylighting analysis, and reportage.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Kokhanok Mini-grid Business Case

A business case analysis was performed for the Village of Kokhanok. The business case analysis evaluated the optimal case from the technical analysis performed by the National Renewable Energy. The optimal case provided for repairing the two Vestas 17 (90 kW) wind turbine controllers and added electric thermal stoves and a battery. The project cost 0.5 million. The direct cost of electricity would likely decline from 0.69/kWh to 0.39/kWh. The direct costs don’t include administrative and distribution costs. The repair of controller and the addition of electric stoves reduced fuel consumption by 63% or approximately 22,000 gallons. The reduction in cost provides an opportunity for the Kokhanok Village Council to obtain financing through grants and loans to install renewable energy and reduce diesel fuel consumption to the cooperative

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

An Efficient Algorithm for Automatic Structure Optimization in X-ray Standing-Wave Experiments

We present that x-ray standing-wave photoemission experiments involving multilayered samples are emerging as unique probes of the buried interfaces that are ubiquitous in current device and materials research. Such data require for their analysis a structure optimization process comparing experiment to theory that is not straightforward. In this work, we present a new computer program for optimizing the analysis of standing-wave data, called SWOPT, that automates this trial-and-error optimization process. The program includes an algorithm that has been developed for computationally expensive problems: so-called black-box simulation optimizations. It also includes a more efficient version of the Yang X-ray Optics Program (YXRO) [Yang, S.-H., Gray, A.X., Kaiser, A.M., Mun, B.S., Sell, B.C., Kortright, J.B., Fadley, C.S., J. Appl. Phys. 113, 1 (2013)] which is about an order of magnitude faster than the original version. Human interaction is not required during optimization. We tested our optimization algorithm on real and hypothetical problems and show that it finds better solutions significantly faster than a random search approach. The total optimization time ranges, depending on the sample structure, from minutes to a few hours on a modern laptop computer, and can be up to 100x faster than a corresponding manual optimization. Finally, these speeds make the SWOPT program a valuable tool for realtime analyses of data during synchrotron experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2016

TH-E-209-02: Dose Monitoring and Protocol Optimization: The Pediatric Perspective

Radiation dose monitoring solutions have opened up new opportunities for medical physicists to be more involved in modern clinical radiology practices. In particular, with the help of comprehensive radiation dose data, data-driven protocol management and informed case follow up are now feasible. Significant challenges remain however and the problems faced by medical physicists are highly heterogeneous. Imaging systems from multiple vendors and a wide range of vintages co-exist in the same department and employ data communication protocols that are not fully standardized or implemented making harmonization complex. Many different solutions for radiation dose monitoring have been implemented by imaging facilities over the past few years. Such systems are based on commercial software, home-grown IT solutions, manual PACS data dumping, etc., and diverse pathways can be used to bring the data to impact clinical practice. The speakers will share their experiences with creating or tailoring radiation dose monitoring/management systems and procedures over the past few years, which vary significantly in design and scope. Topics to cover: (1) fluoroscopic dose monitoring and high radiation event handling from a large academic hospital; (2) dose monitoring and protocol optimization in pediatric radiology; and (3) development of a home-grown IT solution and dose data analysis framework. Learning Objectives: Describe the scope and range of radiation dose monitoring and protocol management in a modern radiology practice Review examples of data available from a variety of systems and how it managed and conveyed. Reflect on the role of the physicist in radiation dose awareness.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Chefornak Mini-grid Business Case

A business case analysis was performed for the Village of Chefornak. The business case analysis evaluated the optimal case from the technical analysis performed by the National Renewable Energy using HOMER. The optimal case adds an 800 kW wind plant with 650 kW of electric thermal stoves and a 300 kW battery. The project cost 5.8 million. The direct cost of electricity would likely decline from 0.41/kWh to 0.30/kWh. The direct costs don’t include administrative and distribution costs. The addition of the renewable resources and thermal electric stoves reduced total fuel consumption by more almost 80% or approximately 103,000 gallons. The reduction in cost provides an opportunity for Chefornak’s utility, the Naterkaq Light Plant, to obtain financing through grants and loans to install renewable energy and reduce overall fuel consumption to the community.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Multiscale design of nonlinear materials using a Eulerian shape optimization scheme

Motivated by recent advances in manufacturing, the design of materials is the focal point of interest in the material research community. One of the critical challenges in this field is finding optimal material microstructure for a desired macroscopic response. This work presents a computational method for the mesoscale-level design of particulate composites for an optimal macroscale-level response. The method relies on a custom shape optimization scheme to find the extrema of a nonlinear cost function subject to a set of constraints. Three key “modules” constitute the method: multiscale modeling, sensitivity analysis, and optimization. Multiscale modeling relies on a classical homogenization method and a nonlinear NURBS-based generalized finite element scheme to efficiently and accurately compute the structural response of particulate composites using a nonconformal discretization. A three-parameter isotropic damage law is used to model microstructure-level failure. An analytical sensitivity method is developed to compute the derivatives of the cost/constraint functions with respect to the design variables that control the microstructure's geometry. The derivation uncovers subtle but essential new terms contributing to the sensitivity of finite element shape functions and their spatial derivatives. Several structural problems are solved to demonstrate the applicability, performance, and accuracy of the method for the design of particulate composites with a desired macroscopic nonlinear stress-strain response.

42 ENGINEERING↗
DOE OSTI2017

Application of Atmospheric Solids Analysis Probe Mass Spectrometry (ASAP-MS) in Petroleomics: Analysis of Condensed Aromatics Standards, Crude Oil, and Paraffinic Fraction

Atmospheric solids analysis probe mass spectrometry (ASAP-MS) is a powerful tool for analysis of solid and liquid samples. It is an excellent alternative for crude oil analysis without any sample preparation step. Here, ASAP-MS in positive ion mode, ASAP(+)-MS, has been optimized for analysis of condensed aromatics (CA) standards, crude oil, and paraffinic fraction samples using a Synapt G2-S HDMS. Initially, two methodologies were used to access the chemical composition of samples: (1) using a temperature gradient varying from 150 to 600 °C at a heating rate of 150 °C min{sup –1}, and (2) with constant temperature of 300 and 400 °C. ASAP(+)-MS ionized many compounds with a typical petroleum profile, showing a greater signals range of m/z 250–1300 and 200–1400 for crude oil and paraffin samples, respectively. Such performance, mainly related to the detection of high molecular weight compounds (>1000 Da), is superior to that of other traditional ionization sources, such as ESI, APCI, DART, and DESI. Additionally, the CA standards were identified in both forms: radicals, [M]{sup +•}, and protonated cations, [M + H]{sup +}, with minimum fragmentation. Therefore, ASAP was more efficient in accessing the chemical composition of nonpolar and polar compounds. It is promising in its application with ultrahigh resolution MS instruments, such as FT-ICR MS and Orbitrap, since molecular formulas with greater resolution and mass accuracy (<1 ppm) would be assigned. .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Background-Oriented Schlieren Velocimetry of Helium Coolant Flow in Additively Manufactured Channels

High-pressure helium gas cooling is an attractive solution for thermal management of the fusion blanket first wall, as this coolant is chemically and neutronically inert and separable from hydrogenic species. However, due to the low thermal mass of helium, geometric optimization of these channels is required to provide sufficient cooling at manageable flow rates and pumping burdens. Increasingly, analysis and optimization of these coolant channels rely on computational fluid dynamics (CFD) simulations, and these require relevant experimental data for turbulence model validation. Toward this end, a high-pressure helium gas flow visualization system has been employed to image the flow of helium in flow channels with one-sided heating, mimicking the blanket first wall environment. Flow of helium at 4 MPa pressure and flow rates up to 68 g/s (Reynolds number 57 000) is supplied to rectangular channel test sections, with uniform heating applied to the bottom wall of the channel at heat fluxes varied between roughly 50 and 130 kW/m2. A high-speed camera is used to image index of refraction (IOR) gradients in the fluid via background-oriented schlieren (BOS), and temperature and pressure instrumentation are used to characterize thermal-hydraulic performance of each channel. Cross correlation of time-resolved BOS images is then used to calculate time-averaged 2-D helium velocity fields. Flow in additively manufactured (AM) channels is examined in this manner, including both featureless channels and those containing baffling as a heat transfer enhancement. The flow distribution seen in the featureless case differs significantly from that seen in prior simulations, whereas the flow in the baffled case shows the predicted behavior of flow forced along the heated wall. This augmented flow distribution is seen to increase the heat transfer coefficient in the baffled test section. Here, strategies are discussed for ongoing and future validation of these simulations, with the aim of model deployment for blanket cooling design and optimization.

Additive manufacturing↗
DOE OSTI2024

Techno-economic analysis and network design for CO 2 conversion to jet fuels in the United States

The conversion of carbon dioxide (CO 2 ) into jet fuel holds significant potential for reducing CO 2 emissions, providing an alternative to carbon-based resources, and offering a renewable means of energy storage. The objective of this study is to conduct a techno-economic analysis and optimize the supply chain network for converting CO 2 to jet fuel in the United States, aiming to minimize total costs while assessing the environmental and economic feasibility of two CO 2 conversion pathways. This first pathway is based on Fischer-Tropsch synthesis (FTS), and the other one is based on the valorization and upgrading of light methanol (MeOH). Incorporating spatial and techno-economic data, a mixed-integer linear programming model was developed to select source plants and conversion pathways, locations of conversion refinery sites, and the amount of captured CO 2 across the United States. The optimal results indicate that the FTS pathway is adopted at all selected refineries when the hydrogen price is 1000 dollars/t and the operating cost, mainly electricity used in conversion, is reduced to 5 % of its current level. Under this scenario, the total annual profit is 8 billion dollars, and the net carbon emissions are -88,783,284 tons. The sensitivity analyses reveal that the prices of electricity and hydrogen significantly contribute to total production costs. The CO 2 recycle percentage of the FTS pathway influences the choice of applied pathways at refineries. Additionally, a higher conversion rate holds a substantial promise for reducing the total production cost and can make the MeOH pathway a viable choice.

10 SYNTHETIC FUELS↗
DOE OSTI2017

Light Water Reactor Sustainability Program Status of Adaptive Surrogates within the RAVEN framework

The RAVEN code has been under development at the Idaho National Laboratory since 2012. Its main goal is to create a multi-purpose platform for the deploying of all the capabilities needed for Probabilistic Risk Assessment, uncertainty quantification, data mining analysis and optimization studies. RAVEN has demonstrated a good level of maturity in terms of state-of-art and advanced analysis methodologies. Indeed, in the past year the RAVEN code has been released as open-source project and is available to download (raven.inl.gov) free of charge. The main subject of this report is to show the activities that have been recently accomplished with respect the adaptive surrogate modeling: Implementation of the metric system for the assessment of surrogate model validity; Implementation of cross-validation techniques for the global assessment of surrogate models; Implementation of an automatic infrastructure for switching between a high-fidelity model (e.g. physical code) and a surrogate or set of surrogates; Implementation of a scheme for automatic optimization of surrogate model parameters. The aim of this document is to report the status of the development of methods, within the RAVEN framework, to assess the validity of the predictive capabilities of surrogate models. Indeed, after the construction of a surrogate tight to a certain physical model, it is crucial to assess the goodness of its representation, in order to be confident with its prediction. A cross-validation technique has been employed. This report will highlight the implementation details and proof its correct implementation by an application example. The implementation of a way to assess the predictive capabilities of a surrogate allowed the construction of a RAVEN new entity named “HybridModel” that is aimed to switch between an high-fidelity code and its linked surrogate. In addition, leveraging the optimization algorithms that have been implemented in RAVEN last fiscal year, a new scheme has been developed for automatic tuning of the surrogates’ parameters (e.g. penalty factors in support vector machines).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Optimization of the determinant of the Vandermonde matrix and related matrices

Various techniques for interpolation of data, moment matching in stochastic applications and various methods in numerical analysis can be described using Vandermonde matrices. For this reason the properties of the determinant of the Vandermonde matrix and related matrices are interesting. Here the extreme points of the Vandermonde determinant, and related determinants, on some simple surfaces such as the unit sphere are analyzed, both numerically and analytically. Some results are also visualized in various dimensions. The extreme points of the Vandermonde determinant are also related to the roots of certain orthogonal polynomials such as the Hermite polynomials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Parallel Hybrid Metaheuristics with Distributed Intensification and Diversification for Large-scale Optimization in Big Data Statistical Analysis

Important insights into many problems that are traditionally analyzed via statistical models can be obtained by re-formulating and evaluating within a large-scale optimization framework. The theoretical underpinnings of the statistical model often shift the goal of the solution space traversal from a traditional search for a single optimal solution to a traversal with the purpose of yielding a set of high quality, independent solutions. We examine statistical frameworks with astronomical solution spaces where the independence requirement constitutes a significant additional challenge for standard optimization methodologies. We design a hybrid metaheuristic with specialized intensification and diversification protocols in the base search algorithm. We extend our algorithm to the high-performance-computing realm using the Stampede2 supercomputer. We experimentally demonstrate the effectiveness of our algorithm to utilize multiple processors to collaboratively hill climb, broadcast messages to one another regarding landscape characteristics, diversify across the solution landscape, and request aid in climbing particularly difficult peaks.

Cho, Wendy K. Tam↗
DOE OSTI2018

ADAPTIVE SURROGATES WITHIN THE RAVEN FRAMEWORK FOR DYNAMIC PROBABILISTIC RISK ASSESSMENT ANALYSIS

The RAVEN code has been under development at the Idaho National Laboratory since 2012. Its main goal is to create a multi-purpose platform for the deploying of all the capabilities needed for Probabilistic Risk Assessment (PRA), Uncertainty Quantification (UQ), data mining analysis and optimization studies. RAVEN has demonstrated a good level of maturity in terms of state-of-art and advanced analysis methodologies. In the past year the RAVEN code has been released as open-source project and is available to download (raven.inl.gov) free of charge. The main subject of this paper is to present a new system within the RAVEN framework to drastically accelerate PRA and UQ analysis using acceleration schemes based on surrogate modeling. This system is based on the heavy usage of surrogate modeling and artificial intelligence algorithms, able to emulate the response of a physical system in closed domains (domains where the surrogate models have been constructed from). The aim of this paper is to show to the community how the employment of surrogate modeling techniques can be a viable solution for the current and future challenges in terms of PRA, UQ and Safety Margins characterizations. In addition, in this manuscript it is presented the construction of a RAVEN new entity named “HybridModel” that is aimed to switch between a high-fidelity code and its linked surrogate, accelerating the PRA and UQ processes without largely reducing the accuracy of the results of the analyses. All these new capabilities will be shown with an application example about a Station Black Out scenario for a prototypical Pressurized Water Reactor (modeled with RELAP5-3D).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Shungnak Mini-grid Business Case

A business case analysis was performed for the Village of Shungnak. The business case analysis evaluated the optimal case from the technical analysis performed by the Sandia National Laboratory using Microgrid Design Toolkit (MDT). The optimal case adds a 500 kW wind plant, 100 kW of solar photovoltaics (PV), 100 kW diesel and 46 kW of electric thermal stoves. The project cost 4.3 million. The direct cost of electricity would likely decline from 0.63/kWh to 0.55/kWh. The direct costs don’t include administrative and distribution costs. The addition of the renewable resources reduced diesel fuel consumption by more than 74% or approximately 96,000 gallons. The reduction in cost provides an opportunity for Alaska Village Electric Cooperative to obtain financing through grants and loans to install renewable energy and reduce diesel fuel consumption to the cooperative.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Design Optimization for Weighted Conduction Loss Minimization in a Dual-Active-Bridge-Based PV Microinverter

This manuscript presents a harmonic-superposition based frequency-domain approach for analysis and optimal design of a single-stage DAB-based DC-AC converter used in low-voltage DC to high voltage AC applications, such as PV microinverter. Specifically, two topological variations and correspondingly different modulation strategies involving up to four control variables (three phase shifts and switching frequency) are analyzed. Optimal trajectories of control variables are determined that result in minimized transformer RMS current at a given average power, while enforcing near-uniform ZVS. To make the design process holistic, an outer optimization loop is used to determine optimal values for the power transfer inductance (integrated as the transformer’s leakage inductance) and turns ratio, which minimize the weighted-average conduction loss contribution to the microinverter’s CEC efficiency. Based on the optimization analyses, a 400 W microinverter prototype is built and experimental results at one operating point are presented, achieving a measured efficiency of 92.8%.

14 SOLAR ENERGY↗
DOE OSTI2014

Fourier Transform-Plasmon Waveguide Spectroscopy: A Nondestructive Multifrequency Method for Simultaneously Determining Polymer Thickness and Apparent Index of Refraction

Fourier transform (FT)-plasmon waveguide resonance (PWR) spectroscopy measures light reflectivity at a waveguide interface as the incident frequency and angle are scanned. Under conditions of total internal reflection, the reflected light intensity is attenuated when the incident frequency and angle satisfy conditions for exciting surface plasmon modes in the metal as well as guided modes within the waveguide. Expanding upon the concept of two-frequency surface plasmon resonance developed by Peterlinz and Georgiadis [ Opt. Commun. 1996, 130, 260], the apparent index of refraction and the thickness of a waveguide can be measured precisely and simultaneously by FT-PWR with an average percent relative error of 0.4%. Measuring reflectivity for a range of frequencies extends the analysis to a wide variety of sample compositions and thicknesses since frequencies with the maximum attenuation can be selected to optimize the analysis. Additionally, the ability to measure reflectivity curves with both p- and s-polarized light provides anisotropic indices of refraction. FT-PWR is demonstrated using polystyrene waveguides of varying thickness, and the validity of FT-PWR measurements are verified by comparing the results to data from profilometry and atomic force microscopy (AFM).

36 MATERIALS SCIENCE↗
DOE OSTI2024

Real-time breath analysis towards a healthy human breath profile

Abstract The direct analysis of molecules contained within human breath has had significant implications for clinical and diagnostic applications in recent decades. However, attempts to compare one study to another or to reproduce previous work are hampered by: variability between sampling methodologies, human phenotypic variability, complex interactions between compounds within breath, and confounding signals from comorbidities. Towards this end, we have endeavored to create an averaged healthy human ‘profile’ against which follow-on studies might be compared. Through the use of direct secondary electrospray ionization combined with a high-resolution mass spectrometry and in-house bioinformatics pipeline, we seek to curate an average healthy human profile for breath and use this model to distinguish differences inter- and intra-day for human volunteers. Breath samples were significantly different in PERMANOVA analysis and ANOSIM analysis based on Time of Day, Participant ID, Date of Sample, Sex of Participant, and Age of Participant ( p < 0.001). Optimal binning analysis identify strong associations between specific features and variables. These include 227 breath features identified as unique identifiers for 28 of the 31 participants. Four signals were identified to be strongly associated with female participants and one with male participants. A total of 37 signals were identified to be strongly associated with the time-of-day samples were taken. Threshold indicator taxa analysis indicated a shift in significant breath features across the age gradient of participants with peak disruption of breath metabolites occurring at around age 32. Forty-eight features were identified after filtering from which a healthy human breath profile for all participants was created.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Technologies for pre-screening IAEA swipe samples

During the course of International Atomic Energy Agency (IAEA) inspections, many samples are taken for the purpose of verifying the declared facility activities and identifying any possible undeclared activities. One of these sampling techniques is the environmental swipe sample. Due to the large number of samples collected, and the amount of time that is required to analyze them, prioritizing these swipes in the field or upon receipt at the Network of Analytical Laboratories (NWAL) will allow sensitive or mission-critical analyses to be performed sooner. As a result of this study, technologies were placed into one of three categories: recommended, promising, or not recommended. Both neutron activation analysis (NAA) and X-ray fluorescence (XRF) are recommended for further study and possible field deployment. These techniques performed the best in initial trials for pre-screening and prioritizing IAEA swipes. We learned that for NAA more characterization of cold elements (such as calcium and magnesium) would need to be emphasized, and for XRF it may be appropriate to move towards a benchtop XRF versus a handheld XRF due to the increased range of elements available on benchtop equipment. Promising techniques that will require additional research and development include confocal Raman microscopy, fluorescence microscopy, and infrared (IR) microscopy. These techniques showed substantive responses to uranium compounds, but expensive instrumentation upgrades (confocal Raman) or university engagement (fluorescence microscopy) may be necessary to investigate the utility of the techniques completely. Point-and-shoot (handheld) Raman and attenuated total reflectance–infrared (ATR-IR) measurements are not recommended, as they have not shown enough promise to continue investigations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗