Results for “Performance analysis” — Page 36

DOE OSTI2018

Synthesis, Fabrication and Characterization of ZnO-Based Thin Films Prepared by Sol–Gel Process and H{sub 2} Gas Sensing Performance

In this paper, an attempt is made to deposit ZnO thin films using sol–gel process followed by dip-coating method on p-silicon (100) substrates for intended application as a hydrogen gas sensor owing to the low toxic nature and thermal stability of ZnO. The thin films are annealed under annealing temperatures of 350, 450 and 550 °C for 25 min. The crystalline quality of the fabricated thin films is then analyzed by field-emission scanning electron microscopy and transmission electron microscope. The gas sensing performance analysis of ZnO thin films is demonstrated at different annealing temperatures and hydrogen gas concentrations ranging from 100 to 3000 ppm. Results obtained show that the sensitivity is significantly improved as annealing temperature increases with maximum sensitivity being achieved at 550 °C annealing temperature and operating temperature of 150 °C. Hence, the modified ZnO thin films can be applicable as H{sub 2} gas sensing device showing to the improved performance in comparison with unmodified thin-film sensor.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Automated model generation and parameter estimation of building energy models using an ontology-based framework

This study presents a methodology for automated model generation and parameter estimation of building energy models using semantic modeling and Bayesian estimation. Semantic modeling techniques are used to represent the system components and their interactions, facilitating the automatic generation of a simulation model from dynamic component models. The proposed approach is applied to a case study of a ventilation system where a simulation model is generated, calibrated, and assessed through different performance metrics. These metrics demonstrate the accuracy and reliability of both model point estimates and probabilistic prediction intervals across all model outputs. Overall, the proposed methodology offers a systematic and automated approach to model development and calibration in building energy systems, with potential applications in building performance analysis, monitoring, and optimization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2014

Implementation of Parallel Adaptive-Krylov Exponential Solvers for Stiff Problems

Recently exponential integrators have been receiving increased attention as a means of solving large stiff systems of ODEs. Preliminary performance analysis demonstrated that exponential integrators hold promise compared to state-of-the-art implicit methods. However, much work remains to be done to understand in detail possible computational advantages these methods may offer in practice. This is particularly true for supercomputer-scale problems as there has been very little work on parallelizing exponential methods. In this paper we describe an implementation of a suite of parallel exponential solvers. Additionally, we present some performance tests on four stiff benchmark problems of a particular adaptive-Krylov exponential propagation iterative Runge--Kutta (EPIRK) method from the suite, and compare efficiency with the Newton--Krylov implicit solver CVODE.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Electron holography of devices with epitaxial layers

Applicability of electron holography to deep submicron Si devices with epitaxial layers is limited due to lack of the mean inner potential data and effects of the sample tilt. The mean inner potential V{sub 0} = 12.75 V of the intrinsic epitaxial SiGe was measured by electron holography in devices with Ge content C{sub Ge} = 18%. Nanobeam electron diffraction analysis performed on the same device structure showed that SiGe is strain-free in [220] direction. Our results showed good correlation with simulations of the mean inner potential of the strain-free SiGe using density function theory. A new method is proposed in this paper to correct electron holography data for the overlap of potentials of Si and the epitaxial layer, which is caused by the sample tilt. The method was applied to the analysis of the dopant diffusion in p-Field-effect Transistor devices with the identical gate length L = 30 nm, which had alternative SiGe geometry in the source and drain regions and was subjected to different thermal processing. Results have helped to understand electrical data acquired from the same devices in terms of dopant diffusion.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Long Duration Energy Storage Viability Survey

Energy storage technologies that can economically store and provide electricity over multi-day and seasonal timescales are likely to be a critical component of a sustainable and resilient energy system. This analysis performs a broad survey of energy storage technologies to find storage media that are promising for these long-duration energy storage applications.

levelized cost of storage↗

DOE OSTI2019

Recovery of Buried Discrete Radioactive Objects by Channel-Specific Analysis of Gamma Scan Data - 19110

During radiological clean-up activities, gamma scan survey data collected from across an industrial site revealed spatially varying concentrations in radioactivity related to naturally occurring soil constituents or dissimilar fill materials that may have been placed at the site. A three-step process was developed to assess the data in order to identify radiation anomalies that most likely could represent small, buried discrete radioactive objects (ROs). The three-step process consists of: (1) define the radiological composition of the site isotopically, (2) spatially parse the data into more homogeneous subgroupings based on the site's radiological composition, and (3) perform analysis of the data subgroupings to identify statistical and spatial population outliers (i.e., radiation anomalies) that otherwise may be masked by the overall variation in the data. Using this process, locations containing buried low-specific activity ROs or higher activity ROs whose radiation is attenuated by soil can be identified and investigated. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2019

Feasibility Assessment of Long-Term Electrical Resistivity Monitoring of a Nitrate Plume

Long-term monitoring solutions at contaminated sites are necessary to track plume migration and evaluate the performance of remediation efforts. Electrical resistivity imaging (ERI) can potentially provide information about plume dynamics; however, the feasibility and likelihood of success is seldom evaluated before conducting a field study. Coupling flow and transport models with geoelectrical models provides a powerful way to assess the potential effectiveness of an actual ERI field campaign. in this paper, we present a coupled approach for evaluating the feasibility of monitoring nitrate migration and remediation using 4D time-lapse ERI at a legacy nuclear waste facility. This kilometer-scale study focuses on depths below the water table (~70 m). A flow and transport model is developed to perform simulations of nitrate migration and removal via a hypothetical pump-and-treat system. A tracer injection is also simulated at the leading edge of the nitrate plume to enhance the conductivity contrast between the native subsurface and the groundwater fluids. Images of bulk conductivity provide limited information concerning plume migration while time-lapse difference images, which remove the static effects of geology, provide more useful information concerning plume dynamics over time. A spatial moment analysis performed on flow and transport and ERI models matches well during the tracer injection; however, inversion regularization smoothing otherwise limits the value in terms of locating the center of mass. We find that the addition of a tracer enables ERI to characterize plume dynamics during pump-and-treat operations, and late-time ERI monitoring provides a conservative estimate of nitrate plume boundaries in this synthetic study.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Blending Pipeline Analysis Tool for Hydrogen (BlendPATH) Documentation and User Manual

The Blending Pipeline Analysis Tool for Hydrogen (BlendPATH) is a flexible, open-source Python tool designed to provide users with case-by-case analysis capabilities to identify the necessary modifications to repurpose existing natural gas transmission pipeline networks to transport hydrogen as a blend of a user-specified volume fraction of hydrogen or as a pure stream and to estimate the associated capital and operating expenditures resulting from those modifications. This tool is intended to be applied during the initial screening stage of a prospective project when pipeline developers compile transmission pipeline technical documentation and history but prior to performing detailed pipeline inspections. Performing analysis with BlendPATH during this initial screening stage can provide the user with an understanding of promising opportunities and probable economic outcomes of repurposing their pipeline network for hydrogen before proceeding with detailed pipeline materials testing and pipeline inspections. BlendPATH consists of multiple modules to simulate, assess, and modify existing natural gas transmission pipeline network designs to be compatible with hydrogen as a blend or pure stream. The tool employs an open-source gas network hydraulic model to simulate existing, user-specified transmission pipeline networks, and it applies ASME B31.12 to assess the pipe segments within these networks for compatibility with hydrogen and to modify the networks to achieve compatibility where the existing infrastructure is inadequate. Users can specify ASME B31.12 design options for pipeline assessment and can select from multiple methods for pipeline modification. This report details the functionalities of BlendPATH Version 2.0.2 and demonstrates an example of applying BlendPATH to a case study. Potential and intended users of this framework include natural gas pipeline developers and operators and researchers at both public and private institutions. BlendPATH is publicly available at https://github.com/NREL/BlendPATH.

08 HYDROGEN↗

DOE OSTI2024

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

Preliminary Safety Analysis for a 400-kW Molten Salt Nuclear Battery

The Molten Salt Nuclear battery (MsNB) is a microreactor based on technology developed and operated at Oak Ridge National Laboratory in the 1960s [1]. But the MsNB has been simplified by removing pumps and valves for improved reliability and safety. The MsNB can safely provide up to 10 MWe of power for up to 10 years and potentially it can be transported by air, truck, and rail thanks due to to its small footprint. A computer model has been developed to represent a prototypical 400-kW MsNB using the ANL system code SAM [2]. The model has been used to produce a reactor thermal-hydraulic performance map and perform analysis of unprotected loss of heat sink accident scenario.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2016

Nekbone performance on GPUs with OpenACC and CUDA Fortran implementations

We present a hybrid GPU implementation and performance analysis of Nekbone, which represents one of the core kernels of the incompressible Navier–Stokes solver Nek5000. The implementation is based on OpenACC and CUDA Fortran for local parallelization of the compute-intensive matrix–matrix multiplication part, which significantly minimizes the modification of the existing CPU code while extending the simulation capability of the code to GPU architectures. Our discussion includes the GPU results of OpenACC interoperating with CUDA Fortran and the gather–scatter operations with GPUDirect communication. We demonstrate performance of up to 552 Tflops on 16, 384 GPUs of the OLCF Cray XK7 Titan.

Computer Science↗

DOE OSTI2020

Comparison between PARFUME and Bison Using the AGR-2 Irradiation Experiment

This report documents comparisons between Fuel Model (PARFUME) model predictions versus Bison for selected compacts from the second irradiation test of the Advanced Gas Reactor (AGR) program that occurred from June 2010 to October 2013 in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). PARFUME is a fuel performance analysis and modeling code, used for evaluating gas-reactor tristructural isotropic (TRISO) coated particle fuel for prismatic, pebble bed, plate, and cylindrical type fuel geometries. PARFUME is an integrated mechanistic computer code that evaluates the thermal, mechanical, and physico-chemical behavior of TRISO coated-fuel particles and the probability for fuel failure given the particle-to-particle statistical variations in physical dimensions and material properties that arise during the fuel fabrication process. Bison is a nuclear fuel performance application built using the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element library (Permann 2020). Bison is capable of modeling multiple fuel forms in a wide variety of dimensions and geometries. It solves coupled nonlinear partial differential equations, including heat conduction, mechanics, fission product species transport etc., in a fully implicit manner. Comparisons between PARFUME and Bison were performed using four compacts from the AGR-2 experiment. Selected outputs were chosen based on their impact on the probability of the SiC layer failing. In general there was good agreement between PARFUME and Bison with the exception of predicting the gap formed between the buffer and IPyC. Further comparisons between PARFUME and Bison are planned to further develop Bison’s capabilities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2019

100 Gbps multiplexed inter-satellite optical wireless communication system

In this paper, the performance analysis of the inter-satellite optical wireless communication system (IsOWC) is carried out in presence of optical space channel. Here the proposed model is a 16×100 Gbps dense multiplexed IsOWC. The dual polarized quadrature phase shift keying (DP-QPSK) modulation is used for improving the optical signal to noise ratio tolerance of the system. Further, the spectral efficiency and the receiver sensitivity is improved by incorporating the coherent orthogonal frequency division multiplexing (CO-OFDM) technique in the proposed IsOWC system. The performance of the system is evaluated by bit error rate (BER), error vector magnitude percentage, received signal power, constellation diagram. A comparative study has been carried out between different modulation techniques such as quadrature phase shift keying and DP-QPSK used in IsOWC system. It is observed that, an inter-satellite distance of 15,600 km is obtained with the proposed model at 100 Gbps for a targeted forward error correction log of BER value of − 2.42 or BER of 3.8×10{sup −3}. The maximum possible data rate for different inter and intra orbit satellite has been calculated. Also, the maximum possible transceiver distance has been calculated for different data rates. The integration of two advanced technologies such as DP-QPSK modulation with CO-OFDM technique in the proposed model may impel the market demands for high bandwidth intensive and high data rate applications.

42 ENGINEERING↗

DOE OSTI2024

Cooled Gas Turbine and Combined Cycle Analysis for NH 3 -CH 4 Fuel Mixes (Up to 100% NH 3 )

In this study, a cooled gas turbine (GT) analysis was conducted for varying levels of ammonia (NH 3 ) blends with methane. The ultimate goal is to have a gas turbine design that can be used for all the fuel blends (including 100% NH 3 ) without any changes to the system. The technological developments in the cooling system, gas turbine design, and materials that will be required for NH 3 combustion were identified and analyzed in this study to develop an advanced gas turbine design for NH 3 fuels. The study includes a combined cycle performance analysis with the NH 3 fuel blends using the advanced gas turbine design developed in this study. A techno-economic analysis was conducted for analyzing the impact of the NH 3 fuels on the levelized cost of electricity and cost sensitivities to fuel price and capacity factor.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2020

Comparative genetics of Enterococcus faecalis intestinal tissue isolates before and after surgery in a rat model of colon anastomosis

We have recently demonstrated that collagenolytic Enterococcus faecalis plays a key and causative role in the pathogenesis of anastomotic leak, an uncommon but potentially lethal complication characterized by disruption of the intestinal wound following segmental removal of the colon (resection) and its reconnection (anastomosis). Here we hypothesized that comparative genetic analysis of E. faecalis isolates present at the anastomotic wound site before and after surgery would shed insight into the mechanisms by which collagenolytic strains are selected for and predominate at sites of anastomotic disruption. Whole genome optical mapping of four pairs of isolates from rat colonic tissue obtained following surgical resection (herein named "pre-op" isolates) and then 6 days later from the anastomotic site (herein named "post-op" isolates) demonstrated that the isolates with higher collagenolytic activity formed a distinct cluster. In order to perform analysis at a deeper level, a single pair of E. faecalis isolates (16A pre-op and 16A post-op) was selected for whole genome sequencing and assembled using a hybrid assembly algorithm. Comparative genomics demonstrated absence of multiple gene clusters, notably a pathogenicity island in the post-op isolate. No differences were found in the fsr-gelE-sprE genes (EF1817-1822) responsible for regulation and production of collagenolytic activity. Analysis of unique genes among the 16A pre-op and post-op isolates revealed the predominance of transporter systems-related genes in the pre-op isolate and phage-related and hydrolytic enzyme-encoding genes in the post-op isolate. Despite genetic differences observed between pre-op and post-op isolates, the precise genetic determinants responsible for their differential expression of collagenolytic activity remains unknown.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Cooled Gas Turbine and Combined Cycle Analysis for H 2 -CH 4 Fuel Mixes (Up to 100% H 2 )

In this study, a cooled gas turbine analysis was conducted for varying levels of hydrogen (H 2 ) blends with the natural gas. The ultimate goal is to have a gas turbine design that can be used for all the fuel blends (including 100% H 2 ) without any changes to the system. The technological developments in the cooling system, gas turbine design and materials that will be required for H 2 combustion were identified and analyzed in this study to develop an advanced gas turbine design for H 2 fuels. The study includes a combined cycle performance analysis with the H 2 fuel blends using the advanced gas turbine design developed in this study. A techno-economic analysis was conducted for analyzing the impact of the H 2 fuels on the levelized cost of electricity and cost sensitivities to fuel price and capacity factor.

03 NATURAL GAS↗

DOE OSTI2021

Propagation Pattern for Moment Representation of the Lattice Boltzmann Method

A propagation pattern for the moment representation of the regularized lattice Boltzmann method (LBM) in three dimensions is presented. Using effectively lossless compression, the simulation state is stored as a set of moments of the lattice Boltzmann distribution function, instead of the distribution function itself. An efficient cache-aware propagation pattern for this moment representation has the effect of substantially reducing both the storage and memory bandwidth required for LBM simulations. This article extends recent work with the moment representation by expanding the performance analysis on central processing unit (CPU) architectures, considering how boundary conditions are implemented, and demonstrating the effectiveness of the moment representation on a graphics processing unit (GPU) architecture.

42 ENGINEERING↗