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DOE OSTI2017

Single-Molecule Fluorescence Spectroscopy of Photosynthetic Systems

Photosynthesis begins when a network of pigment–protein complexes captures solar energy and transports it to the reaction center, where charge separation occurs. When necessary (under low light conditions), photosynthetic organisms perform this energy transport and charge separation with near unity quantum efficiency. Remarkably, this high efficiency is maintained under physiological conditions, which include thermal fluctuations of the pigment–protein complexes and changing local environments. These conditions introduce multiple types of heterogeneity in the pigment–protein complexes, including structural heterogeneity, energetic heterogeneity, and functional heterogeneity. Understanding how photosynthetic light-harvesting functions in the face of these fluctuations requires understanding this heterogeneity, which, in turn, requires characterization of individual pigment–protein complexes. Single-molecule spectroscopy has the power to probe individual complexes. In this review, we present an overview of the common techniques for single-molecule fluorescence spectroscopy applied to photosynthetic systems and describe selected experiments on these systems. We discuss how these experiments provide a new understanding of the impact of heterogeneity on light harvesting and thus how these systems are optimized to capture sunlight under physiological conditions.

14 SOLAR ENERGY↗

DOE OSTI2022

Climatology of the Vertical Profiles of Polarimetric Radar Variables and Retrieved Microphysical Parameters in Continental/Tropical MCSs and Landfalling Hurricanes

Most existing cloud models tend to overestimate the size of cloud ice particles and underestimate their concentration. This emphasizes the need to provide a reliable observational reference to optimize cloud model performance, particularly in areas of high concentration of ice at high altitudes. The dual-polarization radars give the community a unique opportunity to quantify cloud ice with a good accuracy using polarimetric radar retrievals. Here, in this study, we utilize the network of operational WSR-88D radars to build a climatology of the vertical profiles of radar variables, such as radar reflectivity Z, differential reflectivity Z DR , and specific differential phase K DP as well as the radar-retrieved vertical profiles of ice water content (IWC) above the melting layer and liquid water content below it, mean volume diameter D m , and total number concentration N t of ice and liquid particles. Such climatology was created for continental/marine mesoscale convective systems (MCSs) and tropical cyclones including hurricanes. The dataset includes 13 continental MCSs, 10 marine MCSs, and 11 tropical cyclones. Separate statistics of the “background” vertical profiles and the ones associated with high IWC aloft have been obtained in the course of this study. It is shown that continental MCSs exhibit larger size of ice in lower concentration aloft compared to the marine MCSs and especially tropical cyclones/hurricanes. A combination of high KDP and low Z aloft signifies lower D m , higher N t , and often substantial IWC.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

All-atmospheric fabrication of Ag–Cu core–shell nanowire transparent electrodes with Haacke figure of merit >600 × 10–3 Ω−1

Abstract Transparent conducting electrodes (TCEs) are essential components in devices such as touch screens, smart windows, and photovoltaics. Metal nanowire networks are promising next-generation TCEs, but best-performing examples rely on expensive metal catalysts (palladium or platinum), vacuum processing, or transfer processes that cannot be scaled. This work demonstrates a metal nanowire TCE fabrication process that focuses on high performance and simple fabrication. Here we combined direct and plating metallization processes on electrospun nanowires. We first directly metallize silver nanowires using reactive silver ink. The silver catalyzes subsequent copper plating to produce Ag–Cu core–shell nanowires and eliminates nanowire junction resistances. The process allows for tunable transmission and sheet resistance properties by adjusting electrospinning and plating time. We demonstrate state-of-the-art, low-haze TCEs using an all-atmospheric process with sheet resistances of 0.33 Ω sq −1 and visible light transmittances of 86% (including the substrate), leading to a Haacke figure of merit of 652 × 10 –3 Ω −1 . The core–shell nanowire electrode also demonstrates high chemical and bending durability.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Ion aggregation in high salt solutions. III. Computational vibrational spectroscopy of HDO in aqueous salt solutions

The vibrational frequency, frequency fluctuation dynamics, and transition dipole moment of the O—D stretch mode of HDO molecule in aqueous solutions are strongly dependent on its local electrostatic environment and hydrogen-bond network structure. Therefore, the time-resolved vibrational spectroscopy the O—D stretch mode has been particularly used to investigate specific ion effects on water structure. Despite prolonged efforts to understand the interplay of O—D vibrational dynamics with local water hydrogen-bond network and ion aggregate structures in high salt solutions, still there exists a gap between theory and experiment due to a lack of quantitative model for accurately describing O—D stretch frequency in high salt solutions. To fill this gap, we have performed numerical simulations of Raman scattering and IR absorption spectra of the O—D stretch mode of HDO in highly concentrated NaCl and KSCN solutions and compared them with experimental results. Carrying out extensive quantum chemistry calculations on not only water clusters but also ion-water clusters, we first developed a distributed vibrational solvatochromic charge model for the O—D stretch mode in aqueous salt solutions. Furthermore, the non-Condon effect on the vibrational transition dipole moment of the O—D stretch mode was fully taken into consideration with the charge response kernel that is non-local polarizability density. From the fluctuating O—D stretch mode frequencies and transition dipole vectors obtained from the molecular dynamics simulations, the O—D stretch Raman scattering and IR absorption spectra of HDO in salt solutions could be calculated. The polarization effect on the transition dipole vector of the O—D stretch mode is shown to be important and the asymmetric line shapes of the O—D stretch Raman scattering and IR absorption spectra of HDO especially in highly concentrated NaCl and KSCN solutions are in quantitative agreement with experimental results. We anticipate that this computational approach will be of critical use in interpreting linear and nonlinear vibrational spectroscopies of HDO molecule that is considered as an excellent local probe for monitoring local electrostatic and hydrogen-bonding environment in not just salt but also other confined and crowded solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Imaging and dosimetric characteristics of 67 Cu

In recent years the use of beta-emitting radiopharmaceuticals for cancer therapy has expanded rapidly following development of therapeutics for neuroendocrine tumors, prostate cancer, and other oncologic malignancies. One emerging beta-emitting radioisotope of interest for therapy is 67 Cu (t 1/2 : 2.6 d) due to its chemical equivalency with the widely-established positron-emitting isotope 64 Cu (t 1/2 : 12.7 h). Here we evaluate both the imaging and dosimetric characteristics of 67 Cu, as well as producing the first report of SPECT/CT imaging using 67 Cu. To this end, 67 Cu was produced by photon-induced reactions on isotopically-enriched 68 Zn at the Low-Energy Accelerator Facility (LEAF) of Argonne National Laboratory, followed by bulk separation of metallic 68 Zn by sublimation and radiochemical purification by column chromatography. Gamma spectrometry was performed by efficiency-calibrated high-purity germanium (HPGe) analysis to verify absolute activity calibration and establish radionuclidic purity. Absolute activity measurements corroborated manufacturer-recommended dose-calibrator settings and no radionuclidic impurities were observed. Using the Clinical Trials Network anthropomorphic chest phantom, SPECT/CT images were acquired. Medium Energy (ME) SPECT collimation was found to provide the best image quality from the primary 185 keV gamma emission of 67 Cu. Reconstructed images of 67 Cu were similar in quality to images acquired using 177 Lu. Recovery coefficients were calculated and compared against quantitative images of 99m Tc, 177 Lu, and 64 Cu within the same anthropomorphic chest phantom. Production and clinical imaging of 67 Cu appears feasible, and future studies investigating the therapeutic efficacy of 67 Cu-based radiopharmaceuticals are warranted.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2024

Science Use Case Design Patterns for Autonomous Experiments

Connecting scientific instruments and robot-controlled laboratories with computing and data resources at the edge, the Cloud or the high-performance computing (HPC) center enables autonomous experiments, self-driving laboratories, smart manufacturing, and artificial intelligence (AI)-driven design, discovery and evaluation. The Self-driven Experiments for Science / Interconnected Science Ecosystem (INTERSECT) Open Architecture enables science breakthroughs using intelligent networked systems, instruments and facilities with a federated hardware/software architecture for the laboratory of the future. It relies on a novel approach, consisting of (1) science use case design patterns, (2) a system of systems architecture, and (3) a microservice architecture. This paper introduces the science use case design patterns of the INTERSECT Architecture. It describes the overall background, the involved terminology and concepts, and the pattern format and classification. It further offers an overview of the 12 defined patterns and 4 examples of patterns of 2 different pattern classes. It also provides insight into building solutions from these patterns. The target audience are computer, computational, instrument and domain science experts working in the field of autonomous experiments.

Engelmann, Christian↗

DOE OSTI2023

Fission with Exotic Nuclei (Full Technical Report)

Despite its importance for stockpile stewardship or nuclear forensics, data on fission is fragmentary: most experiments have only been performed on stable actinide nuclei and are often incomplete, and theoretical simulations often contain many parameters hard to constrain, which results in large uncertainties. Consequently, nuclear libraries have large gaps for important isotopes. The goal of this project was to prepare to take advantage of the unprecedented yields of radioactive isotopes at the upcoming DOE Facility for Rare Ion Beams and to leverage recent progress in the field of machine learning to develop a comprehensive program of fission studies that could address some of the most pressing problems in nuclear fission over the next several decades. Our project leveraged synergies between experimental nuclear physics, nuclear theory, and data science expertise at LLNL. On the experimental front, our main objective was to develop in-house expertise for inverse kinematics reactions with relativistic beams as well as to field and test new detectors to perform correlated measurements of fission properties. On the theoretical side, the objective was to develop a novel, high-fidelity and scalable approach of fissionfragment calculations based on emulating computationally expensive, quantum-mechanical calculations of nuclear properties with deep neural networks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

INTERSECT Architecture Specification: Use Case Design Patterns (V.0.9)

Connecting scientific instruments and robot-controlled laboratories with computing and data resources at the edge, the Cloud or the high-performance computing (HPC) center enables autonomous experiments, self-driving laboratories, smart manufacturing, and artificial intelligence (AI)-driven design, discovery and evaluation. The Self-driven Experiments for Science / Interconnected Science Ecosystem (INTERSECT) Open Architecture enables science breakthroughs using intelligent networked systems, instruments and facilities with a federated hardware/software architecture for the laboratory of the future. It relies on a novel approach, consisting of (1) science use case design patterns, (2) a system of systems architecture, and (3) a microservice architecture. This document introduces the science use case design patterns of the INTERSECT Architecture. It describes the overall background, the involved terminology and concepts, and the pattern format and classification. It further details the 12 defined patterns and provides insight into building solutions from these patterns. The document also describes the application of these patterns in the context of several INTERSECT autonomous laboratories. The target audience are computer, computational, instrument and domain science experts working in the field of autonomous experiments.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Numerical Investigation of Butterfly Valve Performance in Variable Valve Sizes, Positions and Flow Regimes

Reliability and efficiency of valves are necessary for precise control and sufficient heat-flow to heat application plants for the integrated energy systems of nuclear power plants (NPPs). Strategic Management Analysis Requirement and Technology (SMART) valves’ ability to control flow and assess environmental parameters stands out for these requirements. Their ability to sustain the downstream flow rate, prevent reverse flow, and maintain pressure in the heat transport loop is much more efficient with the integration of sensors and intelligent algorithms. For assessing valve performance and monitoring, mechanical design and operating conditions are two important parameters. In this study, the butterfly valves of three different sizes are simulated with water and steam using STAR-CCM+ in various flow regimes and positions to analyze performance parameters to strategize an automated control system for efficiently balancing the heat–transport network. Also, flow behavior is studied using velocity and pressure fields for valve–body geometry optimization. It can be observed, through performance parameters, that the valves are suitable for operation between 30° and 90° positions with significantly low loss coefficients and high flow coefficients, and the performance parameters follow a certain pattern in both water and steam flow in each scenario.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1991

Reusable Reentry Satellite (RRS): Telemetry, Tracking, and Command (TT/C) Coverage Tradeoff Study

The Reusable Reentry Satellite (RRS) Telemetry, Tracking & Command (TT&C) Coverage Tradeoff Study described herein was performed during Part 1 of the RRS Phase B contract. This report is one of several that describes the results of various trade studies performed to arrive at a recommended design for the RRS satellite system. The overall RRS Phase B Study objective is to design a relatively inexpensive satellite to access space for extended periods of time, with eventual recovery of experiments on Earth. The RRS will be capable of: (1) being launched by a variety of expendable launch vehicles; (2) operating in low earth orbit as a free flying unmanned laboratory; and (3) executing an independent atmospheric reentry and soft landing. The RRS will be designed to be refurbished and reused up to three times a year for a period of 10 years. The expected principal use for such a system is research on the effects of variable gravity (0 to 1.5 g) and radiation on small animals, plants, lower life forms, tissue samples, and materials processes. This Summary Report provides a description of the RRS Telemetry, Tracking & Command Analysis performed to study the ground station coverage available to meet RRS requirements. Concepts were considered that used off-the-shelf technology, had generous margins of capability, and high reliability, were easily maintained, cost effective, and were compatible with existing support networks. From this study, a recommended RRS TT&C configuration will be developed.

Source record↗

NASA NTRS1993

A neural based intelligent flight control system for the NASA F-15 flight research aircraft

A flight control concept that can identify aircraft stability properties and continually optimize the aircraft flying qualities has been developed by McDonnell Aircraft Company under a contract with the NASA-Dryden Flight Research Facility. This flight concept, termed the Intelligent Flight Control System, utilizes Neural Network technology to identify the host aircraft stability and control properties during flight, and use this information to design on-line the control system feedback gains to provide continuous optimum flight response. This self-repairing capability can provide high performance flight maneuvering response throughout large flight envelopes, such as needed for the National Aerospace Plane. Moreover, achieving this response early in the vehicle's development schedule will save cost.

Urnes, James M.↗

NASA NTRS2000

Supporting Scientific Analysis within Collaborative Problem Solving Environments

Collaborative problem solving environments for scientists should contain the analysis tools the scientists require in addition to the remote collaboration tools used for general communication. Unfortunately, most scientific analysis tools have been designed for a "stand-alone mode" and cannot be easily modified to work well in a collaborative environment. This paper addresses the questions, "What features are desired in a scientific analysis tool contained within a collaborative environment?", "What are the tool design criteria needed to provide these features?", and "What support is required from the architecture to support these design criteria?." First, the features of scientific analysis tools that are important for effective analysis in collaborative environments are listed. Next, several design criteria for developing analysis tools that will provide these features are presented. Then requirements for the architecture to support these design criteria are listed. Sonic proposed architectures for collaborative problem solving environments are reviewed and their capabilities to support the specified design criteria are discussed. A deficiency in the most popular architecture for remote application sharing, the ITU T. 120 architecture, prevents it from supporting highly interactive, dynamic, high resolution graphics. To illustrate that the specified design criteria can provide a highly effective analysis tool within a collaborative problem solving environment, a scientific analysis tool that contains the specified design criteria has been integrated into a collaborative environment and tested for effectiveness. The tests were conducted in collaborations between remote sites in the US and between remote sites on different continents. The tests showed that the tool (a tool for the visual analysis of computer simulations of physics) was highly effective for both synchronous and asynchronous collaborative analyses. The important features provided by the tool (and made possible by the specified design criteria) are: 1. The tool provides highly interactive, dynamic, high resolution, 3D graphics. 2. All remote scientists can view the same dynamic, high resolution, 3D scenes of the analysis as the analysis is being conducted. 3. The responsiveness of the tool is nearly identical to the responsiveness of the tool in a stand-alone mode. 4. The scientists can transfer control of the analysis between themselves. 5. Any analysis session or segment of an analysis session, whether done individually or collaboratively, can be recorded and posted on the Web for other scientists or students to download and play in either a collaborative or individual mode. 6. The scientist or student who downloaded the session can, individually or collaboratively, modify or extend the session with his/her own "what if" analysis of the data and post his/her version of the analysis back onto the Web. 7. The peak network bandwidth used in the collaborative sessions is only 1K bit/second even though the scientists at all sites are viewing high resolution (1280 x 1024 pixels), dynamic, 3D scenes of the analysis. The links between the specified design criteria and these performance features are presented.

Watson, Velvin R.↗

NASA NTRS2004

Proposed Development of NASA Glenn Research Center's Aeronautical Network Research Simulator

Accurate knowledge and understanding of data link traffic loads that will have an impact on the underlying communications infrastructure within the National Airspace System (NAS) is of paramount importance for planning, development and fielding of future airborne and ground-based communications systems. Attempting to better understand this impact, NASA Glenn Research Center (GRC), through its contractor Computer Networks & Software, Inc. (CNS, Inc.), has developed an emulation and test facility known as the Virtual Aircraft and Controller (VAC) to study data link interactions and the capacity of the NAS to support Controller Pilot Data Link Communications (CPDLC) traffic. The drawback of the current VAC test bed is that it does not allow the test personnel and researchers to present a real world RF environment to a complex airborne or ground system. Fortunately, the United States Air Force and Navy Avionics Test Commands, through its contractor ViaSat, Inc., have developed the Joint Communications Simulator (JCS) to provide communications band test and simulation capability for the RF spectrum through 18 GHz including Communications, Navigation, and Identification and Surveillance functions. In this paper, we are proposing the development of a new and robust test bed that will leverage on the existing NASA GRC's VAC and the Air Force and Navy Commands JCS systems capabilities and functionalities. The proposed NASA Glenn Research Center's Aeronautical Networks Research Simulator (ANRS) will combine current Air Traffic Control applications and physical RF stimulation into an integrated system capable of emulating data transmission behaviors including propagation delay, physical protocol delay, transmission failure and channel interference. The ANRS will provide a simulation/stimulation tool and test bed environment that allow the researcher to predict the performance of various aeronautical network protocol standards and their associated waveforms under varying density conditions. The system allows the user to define human-interactive and scripted aircraft and controller models of various standards, such as (but not limited to) Very High Frequency Digital Link (VDL) of various modes.

Nguyen, Thanh C.↗

NASA NTRSDate not supplied

Comparison of Prediction Modeling Methodologies for Aeroacoustic Characterization of Hovering sUAS Rotors

This work compared artificial neural network and multivariate orthogonal function modeling methodologies for the prediction and characterization of isolated hovering sUAS rotor aerodynamics and aeroacoustics. Design of Experiments was used to create input feature spaces over 9 input features: the number of rotor blades, rotor size, rotor speed, the amount of blade twist, blade taper ratio, tip chord length, collective pitch, airfoil camber, and airfoil thickness. CAMRAD~II and AARON were executed at the points defined by the input feature space to predict aerodynamic and aeroacoustic quantities. These predicted aerodynamic and aeroacoustic data were then used to generate artificial neural networks and polynomial response surface models. The two prediction model methodologies were evaluated over test data previously unseen by the models, which showed good prediction capabilities for both model types, with slightly lower prediction error for the artificial neural networks. A characterization study was performed, which showed that input features correspondent to the spanwise sectional blade lift and drag were the most significant factors to the aerodynamic thrust and power, respectively. It was also shown that the aeroacoustic quantities were highly dependent on variations in rotor speed and size, which affect the Doppler factor for tonal noise and the spanwise Reynolds number for broadband noise.

Christopher S Thurman↗

DOE OSTI2024

Inaugural Molten Salt Technologies Workshop Powering the Future

The inaugural “Molten Salt Technologies – Powering the Future” Workshop marked a significant convergence of minds from diverse industries, each harnessing molten-salt technologies in innovative ways. Participants from sectors such as solar, geothermal, and advanced nuclear energy, as well as those involved in cutting-edge applications like thermal transport and rare-earth metals extraction, gathered to discuss their shared technical challenges and opportunities. Industry leaders in metal extraction and recycling, alongside experts in high-temperature sensor technology and advanced material manufacturing, also brought their unique perspectives to the table. This workshop served as a crucial platform for these varied industries to delve into the engineering intricacies that molten salt technologies entail. Common challenges such as understanding the thermophysical properties of salts, tackling corrosion mechanisms in harsh environments, and enhancing material resilience under extreme conditions were at the forefront of discussions. These technical sessions highlighted the critical need for cross-industry collaboration to address issues like salt life-cycle process engineering, impurity mitigation, and the development of durable, high-performance materials. By bringing together academia, industry, and representatives from national laboratories and the U.S. Department of Energy (DOE), the workshop facilitated a rich exchange of knowledge and experiences. This interaction not only fostered new partnerships but also strengthened the network among existing collaborators, setting the stage for joint solutions to the complex problems faced by all sectors using molten salt technologies. The event underscored the importance of collaborative efforts in overcoming common engineering challenges and advancing the application of molten-salt technologies across various industries. The workshop not only provided an essential forum for networking and idea exchange but also highlighted the collective drive towards innovative solutions that could benefit multiple fields.

Department of Energy↗

DOE OSTI2024

Inaugural Molten Salt Technologies Workshop Powering the Future

Department of Energy↗

NASA NTRS2020

Aerosol Retrievals from Different Polarimeters During the ACEPOL Campaign Using a Common Retrieval Algorithm

In this paper, we present aerosol retrieval results from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, which was a joint initiative between NASA and SRON – the Netherlands Institute for Space Research. The campaign took place in October–November 2017 over the western part of the United States. During ACEPOL six different instruments were deployed on the NASA ER-2 high-altitude aircraft, including four multi-angle polarimeters (MAPs): SPEX airborne, the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multi-angle SpectroPolarimetric Imager (AirMSPI), and the Research Scanning Polarimeter (RSP). Also, two lidars participated: the High Spectral Resolution Lidar-2 (HSRL-2) and the Cloud Physics Lidar (CPL). Flights were conducted mainly for scenes with low aerosol load over land, but some cases with higher AOD were also observed. We perform aerosol retrievals from SPEX airborne, RSP (410–865 nm range only), and AirMSPI using the SRON aerosol retrieval algorithm and compare the results against AERONET (AErosol RObotic NETwork) and HSRL-2 measurements (for SPEX airborne and RSP). All three MAPs compare well against AERONET for the aerosol optical depth (AOD), with a mean absolute error (MAE) between 0.014 and 0.024 at 440 nm. For the fine-mode effective radius the MAE ranges between 0.021 and 0.028 µm. For the comparison with HSRL-2 we focus on a day with low AOD (0.02–0.14 at 532 nm) over the California Central Valley, Arizona, and Nevada (26 October) as well as a flight with high AOD (including measurements with AOD>1.0 at 532 nm) over a prescribed forest fire in Arizona (9 November). For the day with low AOD the MAEs in AOD (at 532 nm) with HSRL-2 are 0.014 and 0.022 for SPEX and RSP, respectively, showing the capability of MAPs to provide accurate AOD retrievals for the challenging case of low AOD over land. For the retrievals over the smoke plume a reasonable agreement in AOD between the MAPs and HSRL-2 was also found (MAE 0.088 and 0.079 for SPEX and RSP, respectively), despite the fact that the comparison is hampered by large spatial variability in AOD throughout the smoke plume. A good comparison is also found between the MAPs and HSRL-2 for the aerosol depolarization ratio (a measure of particle sphericity), with an MAE of 0.023 and 0.016 for SPEX and RSP, respectively. Finally, SPEX and RSP agree very well for the retrieved microphysical and optical properties of the smoke plume.

Fu, Guangliang↗

DOE OSTI2023

Predicting Failure Using Deep Learning SAND Report

Accurate prediction of ductile failure is critical to Sandia’s NW mission, but the models are computationally heavy. The costs of including high-fidelity physics and mechanics that are germane to the failure mechanisms are often too burdensome for analysts either because of the person-hours it requires to input them or because of the additional computational time, or both. In an effort to deliver analysts a tool for representing these phenomena with minimal impact to their existing workflow, our project sought to develop modern data-driven methods that would add microstructural information to business-as-usual calculations and expedite failure predictions. The goal is a tool that receives as input a structural model with stress and strain fields, as well as a machine-learned model, and output predictions of structural response in time, including failure. As such, our project spent substantial time performing high-fidelity, three-dimensional experiments to elucidate materials mechanisms of void nucleation and evolution. We developed crystal-plasticity finite-element models from the experimental observations to enrich the findings with fields not readily measured. We developed engineering length-scale simulations of replicated test specimens to understand how the engineering fields evolve in the presence of fine-scale defects. Finally, we developed deep learning convolutional neural networks, and graph-based neural networks to encode the findings of the experiments and simulations and make forward predictions in time for structural performance. This project demonstrated the power of data-driven methods for model development, which have the potential to vastly increase both the accuracy and speed of failure predictions. These benefits and the methods necessary to develop them are highlighted in this report. However, many challenges remain to implementing these in real applications, and these are discussed along with potential methods for overcoming them.

97 MATHEMATICS AND COMPUTING↗