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Results for “optimization analysis”

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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Minimization of Measurement Uncertainty in Optical Frequency Domain Reflectometry

Optical frequency domain reflectometry (OFDR) is a technique for interrogating optical fiber sensors to generate relative, quasi-distributed measurements. Although Optical frequency domain reflectometry (OFDR) is increasingly being adopted for aerospace, energy production, and structural monitoring applications, the quantification of uncertainty for OFDR measurements has not been developed beyond sparse empirical relationships. To address this knowledge gap, an uncertainty metric for OFDR measurements was developed. This uncertainty metric was applied to weight the edges between OFDR measurements on directed correlation graphs and analyzed to minimize the cumulative uncertainty. In conclusion, this work is the first to propose an uncertainty metric for OFDR and provides a generalized mathematical framework for optimizing OFDR hardware selection, optical fiber sensor selection, and postprocessing strategy.

42 ENGINEERING↗
DOE OSTI2018

Distributed Link Removal Using Local Estimation of Network Topology

In this paper, we consider the problem of network structure manipulation in the absence of information on the global network topology. In particular, the problem of removing some of links is investigated in order to slow or stop the spread of disease in a network while preserving its connectivity. Existing methods solve this combinatorial problem in a centralized manner and they require the global information of network structure. In this paper, we propose a distributed design algorithm to compute a suboptimal solution to this problem efficiently by mimicking gradient based method, namely by iteratively removing one or multiple links at a time from the network. Specifically, using matrix perturbation analysis we formulate an optimization problem involving the eigenvector associated with the largest eigenvalue of the adjacency matrix and whose solution is equal to a suboptimal solution to the original problem. This strategy also enables us to overcome the combinatorial issue of the problem. Distributed algorithms to estimate the eigenvector and to verify network’s connectivity are then proposed which facilitate us to solve the new optimization problem. In addition, topological insights into the proposed algorithm and optimality of its solution are also discussed. Lastly, the proposed distributed design method is demonstrated and evaluated via several numerical examples.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

A Graphical Model for Fusing Diverse Microbiome Data

This paper develops a Bayesian graphical model for fusing disparate types of count data. The motivating application is the study of bacterial communities from diverse high-dimensional features, in this case, transcripts, collected from different treatments. In such datasets, there are no explicit correspondences between the communities and each corresponds to different factors, making data fusion challenging. We introduce a flexible multinomial-Gaussian generative model for jointly modeling such count data. This latent variable model jointly characterizes the observed data through a common multivariate Gaussian latent space that parameterizes the set of multinomial probabilities of the transcriptome counts. The covariance matrix of the latent variables induces a covariance matrix of co-dependencies between all the transcripts, effectively fusing multiple data sources. We present a computationally scalable variational Expectation-Maximization (EM) algorithm for inferring the latent variables and the parameters of the model. Here, the inferred latent variables provide a common dimensionality reduction for visualizing the data and the inferred parameters provide a predictive posterior distribution. In addition to simulation studies that demonstrate the variational EM procedure, we apply our model to a bacterial microbiome dataset.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Coordinated Optimization of Multiservice Dispatch for Energy Storage Systems with Degradation Model for Utility Applications

The rapid development of energy storage technologies is motivating researchers to understand the possible value of energy storage. This paper evaluates the multiservice dispatch of distribution-sited energy storage systems with realistic degradation models by integrating a multiservice optimization model with a distribution system simulator. This work attempts to define the theoretical value energy storage can bring when multiple value streams are considered in the modeling environment. Use cases presented in this paper deliver multiple services to both distribution and transmission stakeholders that can provide positive net value to the electricity system under prevailing energy storage cost structures. Furthermore, this work was performed in collaboration with a distribution utility to help utility personnel understand the value distributed energy storage can provide by examining different utility use cases without considering implementation costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

SU-C-9A-06: The Impact of CT Image Used for Attenuation Correction in 4D-PET

Purpose: To evaluate the appropriateness of using 3D non-gated CT image for attenuation correction (AC) in a 4D-PET (gated PET) imaging protocol used in radiotherapy treatment planning simulation. Methods: The 4D-PET imaging protocol in a Siemens PET/CT simulator (Biograph mCT, Siemens Medical Solutions, Hoffman Estates, IL) was evaluated. CIRS Dynamic Thorax Phantom (CIRS Inc., Norfolk, VA) with a moving glass sphere (8 mL) in the middle of its thorax portion was used in the experiments. The glass was filled with {sup 18}F-FDG and was in a longitudinal motion derived from a real patient breathing pattern. Varian RPM system (Varian Medical Systems, Palo Alto, CA) was used for respiratory gating. Both phase-gating and amplitude-gating methods were tested. The clinical imaging protocol was modified to use three different CT images for AC in 4D-PET reconstruction: first is to use a single-phase CT image to mimic actual clinical protocol (single-CT-PET); second is to use the average intensity projection CT (AveIP-CT) derived from 4D-CT scanning (AveIP-CT-PET); third is to use 4D-CT image to do the phase-matched AC (phase-matching- PET). Maximum SUV (SUVmax) and volume of the moving target (glass sphere) with threshold of 40% SUVmax were calculated for comparison between 4D-PET images derived with different AC methods. Results: The SUVmax varied 7.3%±6.9% over the breathing cycle in single-CT-PET, compared to 2.5%±2.8% in AveIP-CT-PET and 1.3%±1.2% in phasematching PET. The SUVmax in single-CT-PET differed by up to 15% from those in phase-matching-PET. The target volumes measured from single- CT-PET images also presented variations up to 10% among different phases of 4D PET in both phase-gating and amplitude-gating experiments. Conclusion: Attenuation correction using non-gated CT in 4D-PET imaging is not optimal process for quantitative analysis. Clinical 4D-PET imaging protocols should consider phase-matched 4D-CT image if available to achieve better accuracy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

On the Spatial Localization of Free Electrons in 4H-SiC MOSFETS with an n Channel

The problem of the spatial localization of free electrons in 4H-SiC metal—oxide—semiconductor field effect transistors (MOSFETS) with an accumulation- and inversion-type n channel is theoretically analyzed. The analysis demonstrates that, in optimally designed accumulation transistors (ACCUFETs), the average distance from the surface, at which free electrons are localized, may be an order of magnitude larger than that in inversion MOSFETs. This can make 4H-SiC ACCUFETs advantageous as regards the effective carrier mobility in a conducting channel.

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

What to Support When You’re Compressing

Over the last nearly 20 years, lossy compression has become an essential aspect of HPC applications’ data pipelines, allowing them to overcome limitations in storage capacity and bandwidth and, in some cases, increase computational throughput and capacity. However, with the adoption of lossy compression comes the requirement to assess and control the impact lossy compression has on scientific outcomes. In this work, we take a major step forward in describing the state of practice and by characterizing workloads. We examine applications’ needs and compressors’ capabilities across 9 different supercomputing application domains. We present 24 takeaways that provide best practices for applications, operational impacts for facilities achieving compressed data, and gaps in application needs not addressed by production compressors that point towards opportunities for future compression research.

Error-Bounded Lossy Compression↗
DOE OSTI2017

Raven

RAVEN (Risk Analysis Virtual Environment) is a flexible and multi-purpose probabilistic risk analysis, uncertainty quantification, parameter optimization and data knowledge-discovering framework. https://raven.inl.gov/

Slaughter, AndrewE.↗
DOE OSTI2024

H2Integrate [SWR-23-31]

H2Integrate(H2I) is an open-source Python package for hybrid systems engineering design and technoeconomic analysis. It models and optimizes hybrid energy plants that produce electricity, hydrogen, ammonia, steel, and other products. H2Integrate is designed to be flexible and extensible, allowing users to create their own components and models for various energy systems. The tool currently includes distributed energy generation (wind, solar, wave, tidal), battery storage, hydrogen, ammonia, methanol, and steel technologies. Other elements such as desalination systems, pipelines, compressors, and storage systems can also be included as developed by users. Some modeling capabilities in H2Integrate are provided by integrating existing tools, such as HOPP, PySAM, ORBIT, and ProFAST. The H2Integrate tool is built on top of NASA's OpenMDAO framework, which provides a powerful and flexible environment for modeling and optimization.

King, Jennifer [National Renewable Energy Laborato↗
DOE OSTI2016

On the performance and energy efficiency of sparse linear algebra on GPUs

In this paper we unveil some performance and energy efficiency frontiers for sparse computations on GPU-based supercomputers. We compare the resource efficiency of different sparse matrix–vector products (SpMV) taken from libraries such as cuSPARSE and MAGMA for GPU and Intel’s MKL for multicore CPUs, and develop a GPU sparse matrix–matrix product (SpMM) implementation that handles the simultaneous multiplication of a sparse matrix with a set of vectors in block-wise fashion. While a typical sparse computation such as the SpMV reaches only a fraction of the peak of current GPUs, we show that the SpMM succeeds in exceeding the memory-bound limitations of the SpMV. We integrate this kernel into a GPU-accelerated Locally Optimal Block Preconditioned Conjugate Gradient (LOBPCG) eigensolver. LOBPCG is chosen as a benchmark algorithm for this study as it combines an interesting mix of sparse and dense linear algebra operations that is typical for complex simulation applications, and allows for hardware-aware optimizations. In a detailed analysis we compare the performance and energy efficiency against a multi-threaded CPU counterpart. The reported performance and energy efficiency results are indicative of sparse computations on supercomputers.

Anzt, Hartwig↗
DOE OSTI2022

Proposal and application of ROM-Lasso method for sensitivity coefficient evaluation

We propose a novel method for evaluating sensitivity coefficients of neutronics parameters to cross sections, so-called the reduced-order modeling technique ROM-Lasso. In this method, cross sections of interest are randomly sampled, and corresponding perturbed core analyses are performed. Then, the sensitivity coefficient vector of the higher-level model is expanded via the active subspace bases obtained with the lower-level model whose dimensional complexity is smaller than that of the higher-level model, and the expansion coefficients are estimated by the Lasso regression. A unique feature of the ROM-Lasso method allows the use of different bases optimized for each neutronics parameter. We conducted a verification calculation for an accelerator-driven system and demonstrated that the ROM-Lasso method can reproduce the sensitivity coefficients with a much smaller number of forward calculations than the direct method. The proposed method can be used to practically evaluate sensitivity coefficients. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Stress compensation by deposition of a nonuniform corrective coating

Surface deformation by coating stress is compensated by prefiguring the substrate with a radially nonuniform layer of dense silica. Stresses in the compensation layer and reflector are modeled using finite element analysis to determine the optimal thickness profile, with the deposited coating reducing the surface deformation by 90%. As a result, this process is intended to allow implementation of both the compensation layer and the traditional multilayer coating in a single vacuum cycle.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Improving high temperature resilience of fiber sensor embedded smart components through laser shock peening

This study explores the use of laser shock peening (LSP) to enhance material properties and high-temperature performance of fiber-sensor-fused smart parts fabricated by additive manufacturing (AM) methods. Using embedded fiber sensors as distributed strain gauges, the study demonstrates that LSP can induce compressive strains of up to 130 µε on fiber embedded 1-mm below metal surfaces. The electron backscatter diffraction (EBSD) analysis shows that, with optimized LSP parameters, the metallic matrix undergoes substantial microstructural refinement, resulting in denser structures. Thermal cycling tests showed that the LSP process can increase fiber slippage temperatures by more than 50 °C. This work shows that the LSP process is an effective room-temperature process for enhancing both surface quality and increasing fiber slippage threshold under both thermal and mechanical stress.

Zhong, Shuda [University of Pittsburgh, PA (United↗
DOE OSTI2025

Optimization of laser-induced breakdown spectroscopy for liquid sodium analysis

Next-generation nuclear power reactors based on liquid sodium coolant are in development to improve efficiency and safety. Fast breeder reactors could potentially achieve considerably higher fuel burn-up while producing less nuclear waste compared with current commercial technology. Monitoring of impurities in these types of reactors is important in order to prevent blockage of the cooling system or hazardous reactions due to the high reactivity of sodium with water. In this work, laser-induced breakdown spectroscopy is performed on a liquid sodium sample using a custom-built immersion probe system. The probe provides direct line of sight to the sample vessel in argon atmosphere for laser delivery and signal collection. Signatures of sodium, and impurities such as potassium and oxygen have been obtained. The probe height and immersion have a strong influence on the signal level and stability. Argon flow rates of 2 to 5 liters per minute produce no substantial change in signal, suggesting a steady laminar flowing regime. A high signal-to-noise ratio for impurity elements confirms the suitability of this technique for reliable impurity detection and monitoring in the reactor environment.

Gardette, V. [University of Michigan, Ann Arbor, M↗
DOE OSTI2022

An ecological niche model to predict the geographic distribution of Haemagogus janthinomys, Dyar, 1921 a yellow fever and Mayaro virus vector, in South America

Yellow fever virus (YFV) has a long history of impacting human health in South America. Mayaro virus (MAYV) is an emerging arbovirus of public health concern in the Neotropics and its full impact is yet unknown. Both YFV and MAYV are primarily maintained via a sylvatic transmission cycle but can be opportunistically transmitted to humans by the bites of infected forest dwelling Haemagogus janthinomys Dyar, 1921. To better understand the potential risk of YFV and MAYV transmission to humans, a more detailed understanding of this vector species’ distribution is critical. This study compiled a comprehensive database of 177 unique Hg . janthinomys collection sites retrieved from the published literature, digitized museum specimens and publicly accessible mosquito surveillance data. Covariate analysis was performed to optimize a selection of environmental (topographic and bioclimatic) variables associated with predicting habitat suitability, and species distributions modelled across South America using a maximum entropy (MaxEnt) approach. Our results indicate that suitable habitat for Hg . janthinomys can be found across forested regions of South America including the Atlantic forests and interior Amazon.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Reconstruction of simulated electrostatic potentials by automatic differentiation-based phase retrieval in electron microscopy imaging

Measuring interfacial electrostatic potentials is vital to understanding many fundamental materials properties. A variety of TEM methods exist for measuring electric potentials from the phase shift produced on an electron wave as it passes through a sample. However, most are either experimentally challenging or poorly suited to resolving nanoscale features. Here, we demonstrate the viability of a simple, automatic differentiation-based exit wave reconstruction from a focal series of images to accurately measure nanoscale electric potentials. Here, the analysis suggests that under optimal measurement conditions, electric potentials can be resolved to less than 0.06 V in magnitude and less than 1 nm in spatial extent.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Towards a Stronger Foundation: Digitizing Commercial Buildings with Brick to Enable Portable Advanced Applications

Most large commercial buildings have digital controls for their heating, ventilation, and air-conditioning (HVAC) and lighting systems with the potential to implement advanced control strategies and data analytics. However, advanced control strategies and data analytics are rarely deployed at scale due to non-standard naming conventions and heterogenous building configurations. Semantic metadata standards, like Brick, show promise to proliferate these applications across many buildings, but they have not been widely adopted by industry due to barriers such as perceived risk and unfamiliarity with the technology. This paper describes the workflow we established and evaluated while using it to develop over ten Brick models of existing buildings. Through this process, we observed that digitizing existing commercial buildings is a cost and labor-intensive effort in which understanding the buildings’ data streams is the major bottleneck. Yet, we conclude this investment is worthwhile since various use case applications such as fault detection and diagnostics, thermal comfort analysis, and HVAC control optimization can utilize the same Brick model. The paper also explores the challenges and lessons learned we encountered while creating these data models, such as: 1) difficulties in finding metadata descriptions and relationships for existing buildings; 2) handling missing concepts in the schema needed to model a building; 3) lack of guidance on how to structure the data model or how much detail to include; 4) unfamiliarity with technologies, which makes the learning curve steep for applications developers. Finally, we also describe future directions for semantic metadata research and development to make such transformative technologies more accessible to practitioners.

Roa, Carlos Duarte↗