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DOE OSTI2025

Modal Analysis and Testing of a Cantilever Beam: Results and Guide

This report discusses modal analysis and testing of a cantilever beam including an introduction to modal testing, simulation, analysis, and a comparison of results. An accompanying presentation can be found from the LLNL CASIS website. Modal testing and analysis are essential for characterizing the response of a structure during vibration environments. Determining natural frequencies and mode shapes helps determine whether resonances will be reached during operations and if so, how the structure will respond and how the response can be tuned. The goal of this work is to convey the basics of modal testing and analysis through a simple project. This can be applied later to more complex, applicable structures. This includes a variety of work including data collection, finite element analysis and data processing. For this project a cantilever beam was chosen because it is a simple, well-characterized structure.

42 ENGINEERING↗
DOE OSTI2016

Conditional Tree Reduction in the ADAPT Framework

Probabilistic Risk Assessment (PRA) uses fault tree/event tree analysis to evaluate the environmental impacts of nuclear power plants due to internal or external initiating events. In a fault tree, basic failure events are assembled using primarily And/Or logic to determine the combinations of failures that lead to failure of the system as a whole. An event tree is forward-facing, and begins with a single initiating event. From there the analysis considers what event may occur next, and branches out among the possible configurations of occurrence and non-occurrence of that event. This branching continues until end states are reached. End states may include a safe and stable configuration of the plant, or any number of differing failure states. Both fault and event trees require basic event probabilities as inputs to provide insight on the likelihood of different outcomes. PRA has been applied to nuclear power plants as an analysis tool since the 1975 Reactor Safety Study. In a traditional PRA, the order of events is prescribed by the analyst and each event is typically a binary aleatory uncertainty: occurrence or non-occurrence. Discrete dynamic event tree (DDET) analysis eliminates this subjectivity in ordering of events by using the output of a dynamic system model (simulator) to inform the branching. Branching conditions are triggered by the existence of a relevant plant state in the code, and therefore only occur as physically appropriate. The DDET approach also allows consideration of both epistemic and aleatory uncertainties on a phenomenologically and stochastically consistent platform. A DDET may be orders of magnitude larger than a traditional event tree for the same initiating event, as more of the uncertainty space is likely to be explored and the tree does not require manual assembly. Because of the size, manual inspection of the entire DDET is often infeasible. This problem may be approached from the front by reducing the number of sampled branching values or by online pruning of the tree, thus reducing the total number of branches. Utilizing post-processing techniques to draw actionable insights via clustering has also been proposed. One post-processing tool to reduce the DDET according to user-defined rules has been recently implemented in the Analysis of Dynamic Accident Progression Trees (ADAPT) DDET driver code. The tool creates a 'slice' of the DDET comprised of the set of branches that meet a set of user-input rules, for immediate visualization or for further calculations conditional on the rules being met. This extension is expected to ease analysis of the results of large and complex DDETs, leading to greater applicability of DDETs in PRA. It should be emphasized that this tool is a visualization aide and does not impact the theoretical basis of the DDET approach. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Sensitivity Analysis of Particle-In-Cell Modeling Parameters in Settling Bed, Bubbling Fluidized Bed and Circulating Fluidized Bed

The objective of the work presented is to perform a preliminary sensitivity analysis of particle-in-cell (PIC) model parameters when applied to settling bed, bubbling fluidized bed, and circulating fluidized bed simulations. These examples correspond to widely different flow conditions commonly seen in chemical engineering applications. Simulations were performed using the PIC method in the open-source software Multiphase Flow with Interphase eXchanges (MFiX) developed by the National Energy Technology Laboratory (NETL). As part of the non-intrusive uncertainty quantification (UQ) analysis, simulation campaigns were generated using Nodeworks. Sampling locations or settings for PIC model parameters were determined using the Latin Hypercube method. Response surfaces were created using radial basis functions (RBF), and Sobol’ indices were estimated to quantify the influence of model parameters on the quantities of interest (QoI). This study marks a first step towards systematically determining optimal ranges for model parameters used in MFiX-PIC. Based on limited experience, it is expected that these values would depend strongly on flow conditions. Given the complexity of the multiphase flow systems under analysis, a non-intrusive UQ based approach is used to identify the most influential parameters in each case. This prior knowledge will help in proposing an effective design of experiments (DoE) and determine optimal parameters through techniques such as deterministic or Bayesian calibration, which will be pursued in the future.

42 ENGINEERING↗
DOE OSTI2023

The AXEAP2 program for K β X-ray emission spectra analysis using artificial intelligence

The processing and analysis of synchrotron data can be a complex task, requiring specialized expertise and knowledge. Our previous work addressed the challenge of X-ray emission spectrum (XES) data processing by developing a standalone application using unsupervised machine learning. However, the task of analyzing the processed spectra remains another challenge. Although the non-resonant K β XES of 3 d transition metals are known to provide electronic structure information such as oxidation and spin state, finding appropriate parameters to match experimental data is a time-consuming and labor-intensive process. Here, a new XES data analysis method based on the genetic algorithm is demonstrated, applying it to Mn, Co and Ni oxides. This approach is also implemented as a standalone application, Argonne X-ray Emission Analysis 2 ( AXEAP2 ), which finds a set of parameters that result in a high-quality fit of the experimental spectrum with minimal intervention. AXEAP2 is able to find a set of parameters that reproduce the experimental spectrum, and provide insights into the 3 d electron spin state, 3 d –3 p electron exchange force and K β emission core-hole lifetime.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Synthesis, crystal structure and optical property of three coordination polymer constructed from m-phenylenediacrylate acid

Three new complexes of the wholly deprotonated flexible ligand m-phenylenediacrylate acid (H{sub 2}mpda), namely, [Zn (mpda) (H{sub 2}O)] [1], [Pr{sub 2}(mpda){sub 2}(H{sub 2}O){sub 2}(CHOO){sub 2}] [2], and [Mn{sub 2}(mpda){sub 2} (H{sub 2}O){sub 4}] [3], were synthesized by the solvothermal reaction. The complexes were characterized by IR spectroscopy, thermogravimetric analysis, and X-ray single-crystal diffraction. A mixed sample [Nd(mpda)(H{sub 2}O)(CHOO)·Pr(mpda)(H{sub 2}O)(CHOO)] [2{sup ]} was also synthesized and studied. Compounds [1] and [2] exhibit a selective sensing function with respect to acetone, and they are a potential luminescent sensory material for the selective detection of Zn{sup 2+} and Ni{sup 2+} ions, respectively. Furthermore, the fluorescent changes of compound [1] upon the addition of cations (Fe{sup 3+} and Zn{sup 2+}, Bi{sup 2+} and Zn{sup 2+}) are utilized to construct two logic gates at the molecular level. - Graphical abstract: Three new complexes of flexible ligand m-phenylenedicarboxylic acid were synthesized by solvothermal reaction. Three metal−organic frameworks exhibiting 1D, 2D, 3D structures, respectively. - Highlights: • Three new complexes of m-phenylenedicarboxylic acid were synthesized. • Three metal−organic frameworks exhibiting 1D, 2D, 3D structures, respectively. • [1] and [2] exhibits a very high quenching effect with acetone. • [1] and [2] are a potential luminescent sensory material for Zn{sup 2+}, Ni{sup 2+} ions. • Two logic gates have been constructed using compound [1].

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Assembling Multiple Models Within the RAVEN Framework

RAVEN (Risk Analysis Virtual Environment) is an INL-developed software tool that can be used to identify and increase the safety margin in complex systems. As a generic software framework, RAVEN is designed to perform parametric and probabilistic analysis based on the response of complex system codes. RAVEN is capable of investigating the system response as well as the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused toward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. RAVEN is currently able to construct multi-targets Reduced Order Models (ROMs), which are aimed to represent the response of a system (in a fixed configuration) for multiple Figures of Merits (FOMs) and time-dependent ROMs. These capabilities represent the initial steps for a larger implementation about the interaction of multiple models. In fact, in several cases, multiple models need to interface with each other since the initial conditions of one are dependent on the outcomes of another. To better understand the problem that here is solved, it is useful to consider a simple example: The following problem is considered: a weather forecast simulation code 'a' is used to compute the external (i.e. ambient) temperature in a certain location. A second model 'b' is inquired to compute the average temperature in a room having as boundary condition, among several others, the external ambient temperature. The response of the model 'b' depends on the outcome of the model 'a'. The reported example is only aimed to illustrate the reason why the creation of a framework to make interact different models is a key development for the advancement of RAVEN as a comprehensive calculation flow driver. Before reporting how the ensemble-models have been implemented, it is necessary to briefly describe the representative Model 'entities' that are available in RAVEN.

42 ENGINEERING↗
DOE OSTI2022

Active conformation of the p97-p47 unfoldase complex

The p97 AAA+ATPase is an essential and abundant regulator of protein homeostasis that plays a central role in unfolding ubiquitylated substrates. Here we report two cryo-EM structures of human p97 in complex with its p47 adaptor. One of the conformations is six-fold symmetric, corresponds to previously reported structures of p97, and lacks bound substrate. The other structure adopts a helical conformation, displays substrate running in an extended conformation through the pore of the p97 hexamer, and resembles structures reported for other AAA unfoldases. These findings support the model that p97 utilizes a “hand-over-hand” mechanism in which two residues of the substrate are translocated for hydrolysis of two ATPs, one in each of the two p97 AAA ATPase rings. Proteomics analysis supports the model that one p97 complex can bind multiple substrate adaptors or binding partners, and can process substrates with multiple types of ubiquitin modification.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Preparation and reactivity of macrocyclic rhodium(III) alkyl complexes

We found that the macrocyclic rhodium(II) complexes LRh(H 2 O) 2+ (L = L 1 = cyclam and L 2 = meso-Me-6-cyclam) react with alkyl hydroperoxides RC(CH 3 ) 2 OOH to generate the corresponding rhodium(III) alkyls L(H 2 O)RhR 2+ (R = CH 3 , C 2 H 5 , PhCH 2 ). Methyl and benzyl complexes can also be prepared by bimolecular group transfer from alkyl cobaloximes (dmgH) 2 (H 2 O) CoR and (dmgBF 2 ) 2 (H 2 O) CoR (R = CH 3 , PhCH 2 ) to LRh(H 2 O) 2+ . Moreover, the new complexes were characterized by solution NMR and by crystal structure analysis. They exhibit great stability in aqueous solution at room temperature, but undergo efficient Rh-C bond cleavage upon photolysis.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Let the Good Times Roll – Energy Code Savings into the Future

Long term benefits of energy codes provide valuable information for setting policies, for state adoption, and in evaluating the cost-benefits of energy codes. Pacific Northwest National Laboratory (PNNL) evaluated the long-term impacts associated with energy codes in residential and commercial buildings from 2010 through 2040. The analysis developed and implemented a new methodology that relied on available data and market trends. The study was heavily vetted with key stakeholders including, DOE, Regional Energy Efficiency Organization network (REEOs), ACEEE and others. Several complex streams of information were combined in the analysis, including results from hundreds of simulation models, codes field study data from DOE, floor space data from EIA's Annual Energy Outlook, and data on projected technology improvements from DOE’s Technology Roadmaps. This paper describes the methodology used for the assessment and presents the energy and economic impacts in terms of site energy savings, consumer energy cost savings, and reduced CO2 emissions at the state level and at aggregated national level. The assessment concluded that model energy codes will save $126 billion for consumers on their utility bills, reduce carbon emissions by 841 metric-million tons, and save 12.82 quads of primary energy on a cumulative basis from 2010 through 2040. The results are being used by DOE to underline their role in improving building energy efficiency, by REEOs and states for promoting state code adoption, and by ACEEE and others to perform their own analyses related to energy codes.

buidling energy codes, Impacts of Energy Codes↗
DOE OSTI2024

Progress Towards Microcalorimeter Gamma Spectroscopy Analysis for Nuclear Fuel Separations

The High Efficiency and Resolution Microcalorimeter Spectrometer, 400 pixels (HERMES-400) is an ultra-high resolution gamma-ray spectrometer at Idaho National Laboratory’s Materials and Fuels Complex. HERMES-400 is intended to enable precise nondestructive analysis of advanced fuel cycle materials. Key upgrades and repairs of the instrument were performed this year to improve performance. First, the fourth and final microcalorimeter detector module was installed, meeting the milestone for its integration into the system. Operation with all four modules enables higher detector efficiency than any previous microcalorimeter gamma-ray system. Second, a thinner magnetic shield was installed. This shields the sensitive microcalorimeter pixels from stray magnetic fields while allowing transmission of lower-energy gamma rays, which are important to isotopic analysis. Finally, the cryostat, which provides cooling of the modules to their operating temperature, was found to have a helium coolant leak, which was repaired. HERMES-400 is in a stable state to perform repeated, long-term gamma-ray measurements with good detector efficiency and energy resolution. In FY25, irradiated TRISO fuel and salts from advanced electrochemical recycling techniques are candidates for microcalorimeter measurements. A final upgrade of the magnetic shielding and vibration damping of the system is also planned to maximize the system performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Use of the portable decay gamma source feature in the R2Smesh code system for the accurate estimation of photon radiation dose fields around activated ITER components - Paper 111

The R2Smesh ('Rigorous 2-step') code system, developed by KIT for the determination of shut-down dose rate distribution on mesh grid, can be utilized to provide photon radiation dose field around activated components which are moved from the irradiation site in fusion reactor to another external location. R2Smesh couples MCNP transport calculations and FISPACT inventory calculations through suitable interfaces utilizing MCNP mesh tally capability. Neutron flux and the decay gamma source are provided with high resolution on the mesh grid superimposed to the real geometry to take into account the spatial variations of the flux and the decay gamma source distributions. This feature enables the decay gamma source distribution to be transferred from the irradiation site in the reactor to any other external location for the determination of photon flux and dose rate distributions. In this work, we applied the feature of the portable decay gamma source in R2Smesh code system to a dose rate analysis for a tunnel connecting the ITER tokamak complex building (TCB) and the hot cell facility building (HCFB). This paper presents the use of the portability feature of the decay gamma source in R2Smesh interface code system developed by KIT for a dose rate analysis of the ITER tunnel connecting TCB and HCFB. This application shows that the decay gamma source of the activated components could be transferred successfully from one coordinate system to another coordinate system and superimposed to the geometry of the components. This is very useful when the activated components need to be transported from the reactor to somewhere else for maintenance, testing or storage and the dose rate analysis is requested. Another portable feature, which could convert the 3D decay gamma source distribution generated by R2Smesh system to the MCNP 'SDEF' card source description and avoid the use of source sampling subroutine, is under consideration. With this feature, one decay gamma source result for the specific reactor components could be shared by different institutions who need to use the same decay gamma source for different analysis. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

ANALYSIS OF SAFETY IMPACTS FROM EXTERNAL FLOODING USING THE RISK-INFORMED SAFETY MARGIN CHARACTERIZATION (RISMC) TOOLKIT

The existing fleet of U.S. nuclear power plants is in the process of extending its lifetime and increasing the power generated from these plants via power uprates. In order to evaluate the impact of these factors on the safety of the plant, the Risk-Informed Safety Margin Characterization (RISMC) project aims to provide insight to decision makers through a series of simulations of the plant dynamics for different initial conditions (e.g., probabilistic analysis and uncertainty quantification). This paper demonstrates how Idaho National Laboratory (INL) researchers use the RISMC Toolkit to investigate complex nuclear plant phenomena using RAVEN and RELAP-7. The analysis focused on a highly relevant topic currently facing some nuclear power plants – specifically flooding issues. This research and development looked at challenges to a hypothetical pressurized water reactor, including: (1) a potential loss of off-site power followed by the possible loss of all diesel generators (i.e., a station black-out event), (2) earthquake induced station-blackout, and (3) a potential earthquake induced tsunami flood. The analysis is performed by using a set of codes: a thermal-hydraulic code (RELAP-7), a flooding simulation tool (NEUTRINO) and a stochastic analysis tool (RAVEN) – these are currently under development at INL. Using RAVEN, we were able to perform multiple RELAP-7 simulation runs by changing specific parts of the model in order to reflect specific aspects of different scenarios, including both the failure and recovery of critical components. The simulation employed traditional statistical tools (such as Monte-Carlo sampling) and more advanced machine-learning based algorithms to perform uncertainty quantification in order to understand changes in system performance and limitations as a consequence of power uprate. Qualitative and quantitative results obtained gave a detailed picture of the issues associated with potential accident scenarios. These types of insights can provide useful material for decision makers to perform risk-informed margins management.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Mapping mechanical force propagation through biomolecular complexes

In this paper, we employ single-molecule force spectroscopy with an atomic force microscope (AFM) and steered molecular dynamics (SMD) simulations to reveal force propagation pathways through a mechanically ultrastable multidomain cellulosome protein complex. We demonstrate a new combination of network-based correlation analysis supported by AFM directional pulling experiments, which allowed us to visualize stiff paths through the protein complex along which force is transmitted. Finally, the results implicate specific force-propagation routes nonparallel to the pulling axis that are advantageous for achieving high dissociation forces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2011

Symmetry Elevation and Symmetry Breaking: Keys to Describe and Explain Excitonic Complexes in Semiconductor Quantum Dots

The results of a group theoretical analysis of the excitonic fine structure are presented and compared with spectroscopic data on single quantum dots. The spectral features reveal the signatures of a symmetry higher than the crystal symmetry (C{sub 3v}). A consistent picture of the fine structure patterns for various exciton complexes is obtained with group theory and the concepts of symmetry elevation and symmetry breaking.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Molecular Studies of the Protein Complexes Involving Cis -Prenyltransferase in Guayule ( Parthenium argentatum ), an Alternative Rubber-Producing Plant

Guayule ( Parthenium argentatum ) is a perennial shrub in the Asteraceae family and synthesizes a high quality, hypoallergenic cis -1,4-polyisoprene (or natural rubber; NR). Despite its potential to be an alternative NR supplier, the enzymes for cis -polyisoprene biosynthesis have not been comprehensively studied in guayule. Recently, implications of the protein complex involving cis -prenyltransferases (CPTs) and CPT-Binding Proteins (CBPs) in NR biosynthesis were shown in lettuce and dandelion, but such protein complexes have yet to be examined in guayule. In this work, we identified four guayule genes - three PaCPTs ( PaCPT1-3 ) and one PaCBP , whose protein products organize PaCPT/PaCBP complexes. Co-expression of both PaCBP and each of the PaCPTs could complemented the dolichol (a short cis -polyisoprene)-deficient yeast, whereas the individual expressions could not. Microsomes from the PaCPT/PaCBP -expressing yeast efficiently incorporated 14 C-isopentenyl diphosphate into dehydrodolichyl diphosphates; however, NR with high molecular weight could not be synthesized in in vitro assays. Furthermore, co-immunoprecipitation and split-ubiquitin yeast 2-hybrid assays using PaCPTs and PaCBP confirmed the formation of protein complexes. Of the three PaCPTs , guayule transcriptomics analysis indicated that the PaCPT3 is predominantly expressed in stem and induced by cold-stress, suggesting its involvement in NR biosynthesis. The comprehensive analyses of these PaCPTs and PaCBP here provide the foundational knowledge to generate a high NR-yielding guayule.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Sensitive Top-Down Proteomics Analysis of a Low Number of Mammalian Cells Using a Nanodroplet Sample Processing Platform

Top-down proteomics is a powerful tool for characterizing genetic variations and post-translational modifications at intact protein level. That being said, one significant technical gap of top-down proteomics is the inability to analyze low amount of biological samples, which limits its access to isolated rare cells, fine-needle aspiration biopsies, and tissue substructures. Herein, we developed an ultrasensitive top-down platform by incorporating a microfluidic sample preparation system, termed nanoPOTS (Nanodroplet Processing in One pot for Trace Samples), into a top-down proteomics workflow. A unique combination of a nonionic detergent dodecyl-ß-D-maltopyranoside (DDM) with urea as protein extraction buffer significantly improved both protein extraction efficiency and sample recovery. We hypothesize that the DDM detergent improves protein recovery by efficiently reducing non-specific adsorption of intact proteins on container surfaces, while urea serves as a strong denaturant to disrupt noncovalent complexes and release intact proteins for downstream analysis. The nanoPOTS-based top-down platform reproducibly and quantitatively identified ~170 to ~620 proteoforms from ~70 to ~770 HeLa cells containing ~10 to ~115 ng of total protein. A variety of post-translational modifications including acetylation, myristoylation, and iron binding were identified using only less than 800 cells. We anticipate the nanoPOTS top-down proteomics platform will be broadly applicable in biomedical researches, particularly where clinical specimens are not available in amounts amenable to standard workflows.

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

Visual‐Analytics Bridge Complexity and Accessibility for Robust Urban Water Planning

Urban water resources planning is complicated by unprecedented uncertainty in supply and demand. Real‐world planning often simplifies the full range of uncertainty faced by a system into a limited set of deterministic scenarios to enhance accessibility for decision‐makers and the public. However, overlooking uncertainty can expose the system to failures. On the other end of the spectrum, academically developed tools for scenario analysis rigorously quantify the combined effects of multiple sources of uncertainty, but the practical application of these models is limited by the challenges of information visualization and communication of results. In short, municipal water supply planners lack access to planning frameworks that effectively integrate a rigorous treatment of uncertainty with accessible, user‐friendly visual and interactive tools to enhance user accessibility. In this work, we fill this gap by proposing Visual‐Robust Decision Making, and demonstrate an application for the city of Santa Barbara (SB), CA. Santa Barbara faces multiple uncertainties from pending state and federal regulations to changing hydrology and water demand. The city seeks to increase its water portfolio robustness by expanding its seawater desalination plant, but must decide how much capacity to add. We introduce computational tools that assess uncertainty across nine uncertain drivers identified with the help of water planners in SB. To allow public participation in the desalination expansion decision, we develop interactive visual‐analytics to aid decision‐makers and stakeholders in navigating complex scenario analysis outcomes. Our results quantify the tradeoffs between increased capacity and system robustness and aim to enhance participation and uncertainty characterization of urban water planning efforts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗