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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Aeroelastic Modeling for Distributed Wind Turbines: March 11, 2021 - November 10, 2021

Aeroelastic modeling (AM) is the primary methodology for structural and performance assessment of any wind turbine whereby providing an understanding of the impact of design parameters on its loading and power response before witnessing it in the field. Despite these advantages, the use of AM in the Distributed Wind Technology (DWT) sector is limited, especially within the less established manufacturers. This project represents an in-depth assessment of the status of AM and its role within the Standards for the DWT industry. The study gathered input and feedback from a large number of national and international stakeholders, reviewed technical strengths and weaknesses of the current edition of the design standards, analyzed recent industry workshops' and meetings' minutes, collected publicly available AM templates, and provided an evaluation of the existing AM codes. The study achieved several goals including providing strategies for the load assessment categorization of turbines based on rotor swept area and archetype, and guidance for AM verification and validation (V&V), which includes discussions of measurement requirements and a sample test-plan useful for future V&V campaigns and design standard development. This document summarizes the different tasks conducted in the course of the project and highlights the steps required to improve the AM adoption based on a multifaceted approach that encompasses: 1) augmenting AM software capabilities, 2) publishing AM best-practices and design-basis, 3) creating new model templates, 4) providing guidance for V&V of codes and specific turbine models leveraging field testing best-practice, and 5) addressing weaknesses in the current standards. Many of the future objectives identified in this study could leverage NREL's upcoming testing campaigns of three modern distributed wind turbines. Recommendations within this study will advance the value and the ease-of-use of AM, thereby allowing the industry to better capitalize this underutilized tool resulting in a more efficient design process, an easier path to certification, and overall better and more distributed reliable wind turbine products.

17 WIND ENERGY↗
NASA NTRS2011

Development of Benchmark Examples for Static Delamination Propagation and Fatigue Growth Predictions

The development of benchmark examples for static delamination propagation and cyclic delamination onset and growth prediction is presented and demonstrated for a commercial code. The example is based on a finite element model of an End-Notched Flexure (ENF) specimen. The example is independent of the analysis software used and allows the assessment of the automated delamination propagation, onset and growth prediction capabilities in commercial finite element codes based on the virtual crack closure technique (VCCT). First, static benchmark examples were created for the specimen. Second, based on the static results, benchmark examples for cyclic delamination growth were created. Third, the load-displacement relationship from a propagation analysis and the benchmark results were compared, and good agreement could be achieved by selecting the appropriate input parameters. Fourth, starting from an initially straight front, the delamination was allowed to grow under cyclic loading. The number of cycles to delamination onset and the number of cycles during stable delamination growth for each growth increment were obtained from the automated analysis and compared to the benchmark examples. Again, good agreement between the results obtained from the growth analysis and the benchmark results could be achieved by selecting the appropriate input parameters. The benchmarking procedure proved valuable by highlighting the issues associated with the input parameters of the particular implementation. Selecting the appropriate input parameters, however, was not straightforward and often required an iterative procedure. Overall, the results are encouraging but further assessment for mixed-mode delamination is required.

Kruger, Ronald↗
NASA NTRS2011

Development and Application of Benchmark Examples for Mode II Static Delamination Propagation and Fatigue Growth Predictions

The development of benchmark examples for static delamination propagation and cyclic delamination onset and growth prediction is presented and demonstrated for a commercial code. The example is based on a finite element model of an End-Notched Flexure (ENF) specimen. The example is independent of the analysis software used and allows the assessment of the automated delamination propagation, onset and growth prediction capabilities in commercial finite element codes based on the virtual crack closure technique (VCCT). First, static benchmark examples were created for the specimen. Second, based on the static results, benchmark examples for cyclic delamination growth were created. Third, the load-displacement relationship from a propagation analysis and the benchmark results were compared, and good agreement could be achieved by selecting the appropriate input parameters. Fourth, starting from an initially straight front, the delamination was allowed to grow under cyclic loading. The number of cycles to delamination onset and the number of cycles during delamination growth for each growth increment were obtained from the automated analysis and compared to the benchmark examples. Again, good agreement between the results obtained from the growth analysis and the benchmark results could be achieved by selecting the appropriate input parameters. The benchmarking procedure proved valuable by highlighting the issues associated with choosing the input parameters of the particular implementation. Selecting the appropriate input parameters, however, was not straightforward and often required an iterative procedure. Overall the results are encouraging, but further assessment for mixed-mode delamination is required.

Krueger, Ronald↗
DOE OSTI2024

Profiling expression strategies for a type III polyketide synthase in a lysate-based, cell-free system

Abstract Some of the most metabolically diverse species of bacteria (e.g., Actinobacteria) have higher GC content in their DNA, differ substantially in codon usage, and have distinct protein folding environments compared to tractable expression hosts like Escherichia coli . Consequentially, expressing biosynthetic gene clusters (BGCs) from these bacteria in E. coli often results in a myriad of unpredictable issues with regard to protein expression and folding, delaying the biochemical characterization of new natural products. Current strategies to achieve soluble, active expression of these enzymes in tractable hosts can be a lengthy trial-and-error process. Cell-free expression (CFE) has emerged as a valuable expression platform as a testbed for rapid prototyping expression parameters. Here, we use a type III polyketide synthase from Streptomyces griseus , RppA, which catalyzes the formation of the red pigment flaviolin, as a reporter to investigate BGC refactoring techniques. We applied a library of constructs with different combinations of promoters and rppA coding sequences to investigate the synergies between promoter and codon usage. Subsequently, we assess the utility of cell-free systems for prototyping these refactoring tactics prior to their implementation in cells. Overall, codon harmonization improves natural product synthesis more than traditional codon optimization across cell-free and cellular environments. More importantly, the choice of coding sequences and promoters impact protein expression synergistically, which should be considered for future efforts to use CFE for high-yield protein expression. The promoter strategy when applied to RppA was not completely correlated with that observed with GFP, indicating that different promoter strategies should be applied for different proteins. In vivo experiments suggest that there is correlation, but not complete alignment between expressing in cell free and in vivo. Refactoring promoters and/or coding sequences via CFE can be a valuable strategy to rapidly screen for catalytically functional production of enzymes from BCGs, which advances CFE as a tool for natural product research.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Global Sensitivity Measures from Given Data

Simulation models support managers in the solution of complex problems. International agencies recommend uncertainty and global sensitivity methods as best practice in the audit, validation and application of scientific codes. However, numerical complexity, especially in the presence of a high number of factors, induces analysts to employ less informative but numerically cheaper methods. This work introduces a design for estimating global sensitivity indices from given data (including simulation input–output data), at the minimum computational cost. We address the problem starting with a statistic based on the L1-norm. A formal definition of the estimators is provided and corresponding consistency theorems are proved. The determination of confidence intervals through a bias-reducing bootstrap estimator is investigated. The strategy is applied in the identification of the key drivers of uncertainty for the complex computer code developed at the National Aeronautics and Space Administration (NASA) assessing the risk of lunar space missions. We also introduce a symmetry result that enables the estimation of global sensitivity measures to datasets produced outside a conventional input–output functional framework.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

A Specific miRNA Signature Correlates With Complete Pathological Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer

Purpose: MicroRNAs (miRNAs) are small, noncoding RNA molecules that can be down- or upregulated in colorectal cancer and have been associated to prognosis and response to treatment. We studied miRNA expression in tumor biopsies of patients with rectal cancer to identify a specific 'signature' correlating with pathological complete response (pCR) after neoadjuvant chemoradiotherapy. Methods and Materials: A total of 38 T3-4/N+ rectal cancer patients received capecitabine-oxaliplatin and radiotherapy followed by surgery. Pathologic response was scored according to the Mandard TRG scale. MiRNA expression was analyzed by microarray and confirmed by real-time Reverse Transcription Polymerase Chain Reaction (qRT-PCR) on frozen biopsies obtained before treatment. The correlation between miRNA expression and TRG, coded as TRG1 (pCR) vs. TRG >1 (no pCR), was assessed by methods specifically designed for this study. Results: Microarray analysis selected 14 miRNAs as being differentially expressed in TRG1 patients, and 13 were confirmed by qRT-PCR: 11 miRNAs (miR-1183, miR-483-5p, miR-622, miR-125a-3p, miR-1224-5p, miR-188-5p, miR-1471, miR-671-5p, miR-1909 Asterisk-Operator , miR-630, miR-765) were significantly upregulated in TRG1 patients, 2 (miR-1274b, miR-720) were downexpressed. MiR-622 and miR-630 had a 100% sensitivity and specificity in selecting TRG1 cases. Conclusions: A set of 13 miRNAs is strongly associated with pCR and may represent a specific predictor of response to chemoradiotherapy in rectal cancer patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Subject-specific modeling framework for particle deposition using computational fluid dynamics

Quantifying particle deposition and dose in the respiratory tract requires a physiologically realistic representation and reproducible computational workflows. However, existing modeling frameworks, such as the International Commission on Radiological Protection (ICRP) compartmental models and the Multiple Path Particle Dosimetry (MPPD) tool, lack detailed deposition profiles and subject-specific capabilities. The combination of advances in computer vision algorithms applied to the respiratory tract and Computational Fluid and Particle Dynamics (CFPD) allows high-fidelity simulations of particle behavior in anatomically accurate geometries derived from individual CT scans. The segmentation, preprocessing, and file preparation task for a CFPD simulation was often time-consuming, and no prior studies to-date have yet presented a fully automated framework. This work presents a fully automated workflow to obtain individualized particle deposition profiles in the human respiratory tract. The pipeline starts with segmenting upper and lower airway geometries using morphological and deep learning-based methods, generating three-dimensional (3D) models from CT imaging data. Next, a series of algorithms are presented to quality check and prepare the 3D geometry for a CFD or CFPD simulation. The preprocessing step includes correcting geometric artifacts, enforcing a physically consistent mesh, and automatically identifying and capping multiple outlets, which is required for CFD/CFPD simulations. These processed models are then input into open-source (OpenFOAM) or commercial (StarCCM+) CFD solvers, where flow and transient particle transport equations — including turbulence and particle–wall interactions are solved under realistic breathing conditions. Finally, the resulting particle deposition profiles can be integrated with Monte Carlo radiation transport codes and state-of-the-art computational phantoms to assess organ-specific absorbed doses in scenarios of radioactive aerosol inhalation. The presented work streamlines respiratory tract segmentation, preprocessing for CFD/CFPD simulations, and integration with dose assessment workflows, reducing manual intervention and improving access to high-fidelity, subject-specific modeling. The high precision in predicted particle deposition and dose distributions can improve personalized treatment strategies in respiratory medicine and refine dose estimates for radiation protection.

AI↗
DOE OSTI2022

Verification of Bison fission product species conservation under TRISO reactor conditions

When assessing the reliability and predictive capabilities of a simulation tool, code verification is used to ensure that the implemented numerical algorithm is a faithful representation of its underlying mathematical model, including partial differential or integral equations, initial and boundary conditions, and auxiliary relationships. During this process, numerical results in a discrete solution are compared to the analytical solution of the mathematical model. Here, in this paper, the code verification process is applied to one-dimensional spatiotemporal problems that exercise partial differential equation governing the conservation of fission product species (or mass diffusion). Numerical experiments were performed in the Bison fuel performance code to evaluate its predictive capability under various TRISO reactor conditions such as base irradiation and safety heating test conditions for either short- or long-lived fission product species, as well as a case concerning evaporation from the outer surface of a particle. The code predictions were compared with the expected exact results obtained from the analytical expressions, and the fact that they demonstrate the correct analytical behavior provides strong evidence of proper numerical algorithm implementation.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2017

Improving membrane protein expression and function using genomic edits

Expression of membrane proteins often leads to growth inhibition and perturbs central metabolism and this burden varies with the protein being overexpressed. There are also known strain backgrounds that allow greater expression of membrane proteins but that differ in efficacy across proteins. Here, we hypothesized that for any membrane protein, it may be possible to identify a modified strain background where its expression can be accommodated with less burden. To directly test this hypothesis, we used a bar-coded transposon insertion library in tandem with cell sorting to assess genome-wide impact of gene deletions on membrane protein expression. The expression of five membrane proteins (CyoB, CydB, MdlB, YidC, and LepI) and one soluble protein (GST), each fused to GFP, was examined. We identified Escherichia coli mutants that demonstrated increased membrane protein expression relative to that in wild type. For two of the proteins (CyoB and CydB), we conducted functional assays to confirm that the increase in protein expression also led to phenotypic improvement in function. This study represents a systematic approach to broadly identify genetic loci that can be used to improve membrane protein expression, and our method can be used to improve expression of any protein that poses a cellular burden.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

A broadband gamma-ray spectrometry using novel unfolding algorithms for characterization of laser wakefield-generated betatron radiation

We present a high-flux, broadband gamma-ray spectrometry capable of characterizing the betatron radiation spectrum over the photon energy range from 10 keV to 20 MeV with respect to the peak photon energy, spectral bandwidth, and unique discrimination from background radiations, using a differential filtering spectrometer and the unfolding procedure based on the Monte Carlo code GEANT4. These properties are experimentally verified by measuring betatron radiation from a cm-scale laser wakefield accelerator (LWFA) driven by a 1-PW laser, using a differential filtering spectrometer consisting of a 15-filter and image plate stack. The gamma-ray spectra were derived by unfolding the photostimulated luminescence (PSL) values recorded on the image plates, using the spectrometer response matrix modeled with the Monte Carlo code GEANT4. The accuracy of unfolded betatron radiation spectra was assessed by unfolding the test PSL data simulated with GEANT4, showing an ambiguity of less than 20% and clear discrimination from the background radiation with less than 10%. The spectral analysis of betatron radiation from laser wakefield-accelerated electron beams with energies up to 3 GeV revealed radiation spectra characterized by synchrotron radiation with the critical photon energy up to 7 MeV. The gamma-ray spectrometer and unfolding method presented here facilitate an in-depth understanding of betatron radiation from LWFA process and a novel radiation source of high-quality photon beams in the MeV regime.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Power increases using wind direction spatial filtering for wind farm control: Evaluation using FLORIS, modified for dynamic settings

As wind energy plays a growing role in the energy sector, new methods for controlling wind turbines and wind farms to maximize performance are garnering industry interest. A developing body of research treats the entire wind farm as a control system, with individual turbines acting as agents in a network, allowing farm-level objectives to be considered. Two promising developments in this research are wake steering control, which seeks to increase the power generated at a wind farm by directing the wakes of upstream turbines away from downstream ones, and communication-based spatial filtering, which seeks to improve the quality of information used by turbine- and farm-level controllers by combining measurements of the wind field collected at the individual turbines. The latter method has been shown to improve the estimates of wind direction at the turbines; however, the resulting potential for increased power capture warrants further investigation. With this paper, we begin to address this gap by combining wake steering with wind direction spatial filtering. To do so, we present a preliminary method for assessing the power capture of dynamic controllers using wind farm codes designed for time-averaged simulation. This allows us to generate results much more rapidly than would be possible using high-fidelity wind farm simulators and may be useful in many wind farm control design applications.

17 WIND ENERGY↗
DOE OSTI2021

Cost- and Risk-Based Seismic Design Optimization of Nuclear Power Plant Safety Systems

Seismic analysis, design, and qualification of systems, structures, and components (SSCs) is a significant contributor to the capital cost of a nuclear power plant. To reduce capital costs of advanced nuclear power plants and make commercial nuclear energy more competitive, innovations are needed in their structural design and construction, and not just in the reactor core and associated systems. Seismic isolation has been identified as an important cost-cutting technology that enables standardization of equipment across various sites. This paper develops and demonstrates a cost- and risk-based seismic design optimization of a representative safety system in a nuclear power plant with the dual goals of minimizing overnight capital cost and meeting safety goals. The design optimization can also include component seismic isolation, in which case, the optimized design includes a set of equipment that needs to be seismically isolated to minimize capital cost. The open-source codes MASTODON and Dakota are used for seismic probabilistic risk assessment and design optimization, respectively. A generic nuclear facility with a safety system comprising SSCs that are common to nuclear power plants is considered for the demonstration of the design optimization and is assumed to be located at the Idaho National Laboratory site. Generic costs and seismic design cost functions are assumed for the SSCs of the safety system. The sum of the costs of the SSCs is minimized in the optimization process, while the risk of failure of the safety system is provided as a constraint. Furthermore, results show that the optimization process reduces capital costs significantly while automatically prioritizing the safety of SSCs that contribute most to the risk of the safety system.

42 ENGINEERING↗
DOE OSTI2024

Neutronics and Thermo-Fluids Simulation of Generic Pebble-Bed Fluoride-Salt-Cooled High-Temperature Reactor

The fluoride-salt-cooled high-temperature reactor (FHR) is one of the advanced reactors that has been attracting considerable interest from both the research community and the nuclear industry. To help facilitate the nuclear community's familiarity with the FHR, Kairos Power has developed a generic FHR (gFHR) benchmark. In the research performed here, this benchmark was used to assess innovative modeling methods that combine stochastic and deterministic computer codes to perform the design and analysis of the gFHR. Further, the Monte Carlo code Serpent 2 was used to generate few-group cross sections that were then used in the neutron diffusion and thermal-fluids code AGREE to perform full-core neutronics and thermal-fluids steady-state and transient core analysis. The Argonne National Laboratory code SAM was then used to model the gFHR system and to simulate the load-follow operation of the gFHR.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

PolyCheck: Dynamic Verification of Iteration Space Transformations on Affine Programs

High-level compiler transformations, especially loop transformations, are widely recognized as critical optimizations to restructure programs to improve data locality and expose parallelism. Guaranteeing the correctness of program transformations is essential, and to date three main approaches have been developed: proof of equivalence of affine programs, matching the execution traces of programs, and checking bit-by-bit equivalence of the outputs of the programs. Each technique suffers from limitations in either the kind of transformations supported, space complexity, or the sensitivity to the testing dataset. In this paper, we take a novel approach addressing all three limitations to provide an automatic bug checker to verify any iteration reordering transformations on affine programs, including non-affine transformations, with space consumption proportional to the original program data, and robust to arbitrary datasets of a given size. We achieve this by exploiting the structure of affine program control- and data-flow to generate at compile-time lightweight checker code to be executed within the transformed program. Experimental results assess the correctness and effectiveness of our method, and its increased coverage over previous approaches.

affine programs↗
DOE OSTI2023

Ground Water Age Predictor

Machine Learning script to predict groundwater ages based on auxiliary features in a publicly available dataset, based on publicly available software libraries. Code applied to data from the Groundwater Ambient Monitoring and Assessment (GAMA) program in California, including well location and construction information, chemical constituents and isotopic tracers, and land use metrics.

Chakraborty, Indrasis↗
DOE OSTI2013

IMEX-a :

This report presents an efficient and accurate method for integrating a system of ordinary differential equations, particularly those arising from a spatial discretization of partially differential equations. The algorithm developed, termed the IMEX a algorithm, belongs to a class of algorithms known as implicit-explicit (IMEX) methods. The explicit step is based on a fifth order Runge-Kutta explicit step known as the Dormand-Prince algorithm, which adaptively modifies the time step by calculating the error relative to a fourth order estimation. The implicit step, which follows the explicit step, is based on a backward Euler method, a special case of the generalized trapezoidal method. Reasons for choosing both of these methods, along with the algorithm development are presented. In applications that have less stringent accuracy requirements, several other methods are available through the IMEX a toolbox, each of which simplify the fifth order Dormand-Prince explicit step: the third order Bogacki-Shampine method, the second order Midpoint method, and the first order Euler method. The performance of the algorithm is evaluated on to examples. First, a two pawl system with contact is modeled. Results predicted by the IMEX a algorithm are compared to those predicted by six widely used integration schemes. The IMEX a algorithm is demonstrated to be significantly faster (by up to an order of magnitude) and at least as accurate as all of the other methods considered. A second example, an acoustic standing wave, is presented in order to assess the accuracy of the IMEX a algorithm. Finally, sample code is given in order to demonstrate the implementation of the proposed algorithm.

Brake, Matthew Robert↗
DOE OSTI2015

RAVEN Quality Assurance Activities

This report discusses the quality assurance activities needed to raise the Quality Level of Risk Analysis in a Virtual Environment (RAVEN) from Quality Level 3 to Quality Level 2. This report also describes the general RAVEN quality assurance activities. For improving the quality, reviews of code changes have been instituted, more parts of testing have been automated, and improved packaging has been created. For upgrading the quality level, requirements have been created and the workflow has been improved.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

RAVEN Theory Manual

RAVEN is a software framework able to perform parametric and stochastic analysis based on the response of complex system codes. The initial development was aimed at providing dynamic risk analysis capabilities to the thermohydraulic code RELAP-7, currently under development at Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose stochastic and uncertainty quantification platform, capable of communicating with any system code. In fact, the provided Application Programming Interfaces (APIs) allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by input files or via python interfaces. RAVEN is capable of investigating system response and explore input space using various sampling schemes such as Monte Carlo, grid, or Latin hypercube. However, RAVEN strength lies in its system feature discovery capabilities such as: constructing limit surfaces, separating regions of the input space leading to system failure, and using dynamic supervised learning techniques. The development of RAVEN started in 2012 when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework arose. RAVEN’s principal assignment is to provide the necessary software and algorithms in order to employ the concepts developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just to identify the frequency of an event potentially leading to a system failure, but the proximity (or lack thereof) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. peak pressure in a pipe) is exceeded under certain conditions. Most of the capabilities, implemented having RELAP-7 as a principal focus, are easily deployable to other system codes. For this reason, several side activates have been employed (e.g. RELAP5-3D, any MOOSE-based App, etc.) or are currently ongoing for coupling RAVEN with several different software. The aim of this document is to provide a set of commented examples that can help the user to become familiar with the RAVEN code usage.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗