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At least 217 records · Page 12

Real-Time Health Monitoring for Gas Turbine Components Using Online Learning and High-Dimensional Data (Final Report)

Capital-intensive turbomachinery, such as gas turbines and combined cycle plants, are constantly being monitored for performance anomalies, faults, and physical degradation. Although these power-generating assets are equipped with hundreds of sensors, existing monitoring tools can only handle moderate-sized data. As a result, only a handful of aggregate metrics are used to monitor machine health. At the same time, developing advanced tools suitable for large datasets have been restricted by the lack of appropriate data. The objective of this proposal was to demonstrate a Big Data analytics framework for fault detection and diagnosis in gas turbine applications. We develop a predictive analytics framework methodology guided by these experimental data, industrial data from our collaborators, and physics-based models with engineering domain knowledge. Our analytics framework consists of four key components: (1) a data curation process that addresses data storage, data quality assessments, and integrity checks, (2) a feature engineering component that utilizes statistical methods and transformation algorithms guided by physics-based models to extract high-fidelity fault features that can be leveraged for fault detection and classifying fault severities, (3) a Machine Learning-based fault detection and diagnostics algorithms for detecting operational and hardware faults in the combustion and the turbines section. We utilize two industry-class gas turbine component test rigs to generate first of its kind data for critical gas turbine faults with varying severity levels. Advanced gas turbine test facilities will be interrogated using state-of-the-art instrumentation techniques to build fault signatures and data trends for key combustor and turbine faults. Data generated from a combustor test rig (Georgia Tech) and a turbine test rig (Penn State) during both normal operation and with seeded faults serve as the basis for the Big Data sets. The test conditions in the two test facilities include common, critical events that occur in the operation. Utilizing the combustor test rig, we examine two common combustor faults: lean blowout and centerbody degradation. For the turbine section we develop analytic models for monitoring cooling faults in the gas turbine.

20 FOSSIL-FUELED POWER PLANTS↗

Real-Time Health Monitoring for Gas Turbine Components Using Online Learning and High-Dimensional Data

Capital-intensive turbomachinery, such as gas turbines and combined cycle plants, are constantly being monitored for performance anomalies, faults, and physical degradation. Although these power-generating assets are equipped with hundreds of sensors, existing monitoring tools can only handle moderate-sized data. As a result, only a handful of aggregate metrics are used to monitor machine health. At the same time, developing advanced tools suitable for large datasets have been restricted by the lack of appropriate data. The objective of this proposal was to demonstrate a Big Data analytics framework for fault detection and diagnosis in gas turbine applications. We develop a predictive analytics framework methodology guided by these experimental data, industrial data from our collaborators, and physics-based models with engineering domain knowledge. Our analytics framework consists of four key components (1) a data curation process that addresses data storage, data quality assessments, and integrity checks, (2) a feature engineering component that utilizes statistical methods and transformation algorithms guided by physics-based models to extract high-fidelity fault features that can be leveraged for fault detection and classifying fault severities, (3) a Machine Learning-based fault detection and diagnostics algorithms for detecting operational and hardware faults in the combustion and the turbines section. We utilize two industry-class gas turbine component test rigs to generate first of its kind data for critical gas turbine faults with varying severity levels. Advanced gas turbine test facilities will be interrogated using state-of-the-art instrumentation techniques to build fault signatures and data trends for key combustor and turbine faults. Data generated from a combustor test rig (Georgia Tech) and a turbine test rig (Penn State) during both normal operation and with seeded faults serve as the basis for the Big Data sets. The test conditions in the two test facilities include common, critical events that occur in the operation. Utilizing the combustor test rig, we examine two common combustor faults: lean blowout and centerbody degradation. For the turbine section we develop analytic models for monitoring cooling faults in the gas turbine

03 NATURAL GAS↗

Direct Laser Impulse (DLI) System Alignment: Requirements Engineering Project

The National Ignition Facility (NIF) is the world’s largest and most energetic laser, and it is comprised of 192 laser beams that must align onto one target for the purpose of learning about Internal Confinement Fusion (ICF) and High Energy Density (HED) physics. A new NIF capability under development is the Direct Laser Impulse (DLI). The DLI capability will provide a test environment where high pulsed laser energy is delivered to a three-dimensional target. Achieving this delivery to target relies on a precision alignment and positioning of the two redirected NIF beams, as shown in Figure 1. When aligned, the two combined beams—with a frequency converted from infrared (IR) to green laser light, at a fluence (energy per unit area) of roughly 20 joules per square centimeter—will be capable of delivering up to 30 kilojoules of direct, unfocused energy to a one cubic foot target. The 40-cm x 40-cm aligned impulse area at the DLI target interaction plane (TIP) is achieved by using a beam path comprised of pickoff and transport mirrors, frequency conversion crystals, optics serving as environmental barriers, and debris shields. A separate aligned diagnostic beam path is also required for impulse to TIP characterization. Final in-situ alignment is required for the two populated diverted NIF beam paths onto the DLI target as well as the diagnostic optical beam path. Existing NIF alignment subsystems do not offer references that meet DLI’s unique demand. The new DLI Red Box, which has been designed to allow for alignment, has been shown to require deviation from the intended configuration and operational use case to obtain adequate functionality. A systems engineering evaluation has identified a solution that meets the stakeholder requirements while optimizing key performance parameters. The solution, referred to in this document as the Red Box “+” Rotated, was determined to be an improved version of the current DLI Red Box. This system offers improved system repeatability and alignment stability while maintaining similar interfaces and decreasing the demand for engineer/operator interaction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis

With the increasing digitalization of processes throughout the lifecycle of buildings, data exchanged between stakeholders and between building systems has grown significantly. However, a lack of semantic interoperability between data in different systems is still prevalent, hindering the development of applications that can be reused across buildings and limiting the scalability of innovative solutions. Semantics refers to the description of the meaning of the data in a way that can be consistently understood by applications. Recently, several competing initiatives have been developing metadata schemas and ontologies to express this semantic information for different applications in the building domain. This paper systematically reviews these schemas and conducts an analysis of five of them to evaluate their applicability to three high-value use cases for building operations: energy audits, automated fault detection and diagnostics and optimal control. The survey finds 40 schemas published in the last 10 years but but their actual use in industry is difficult to estimate. Among the five selected ontologies, several gaps are highlighted in relation to the three use cases. Recommendations for the future include better harmonization of these initiatives, more centralized repositories and search engines for these schemas as well as better industry engagement to facilitate their adoption.

Smart Building, Sematic, Metadata, Ontology, Data ↗

Inertial dynamics of an interface with interfacial mass flux: Stability and flow fields’ structure, inertial stabilization mechanism, degeneracy of Landau’s solution, effect of energy fluctuations, and chemistry-induced instabilities

This work focuses on the long-standing problem of inertial dynamics of an interface with interfacial mass flux and reports new mechanisms for the interface stabilization and destabilization. The interface is a phase boundary separating fluids of different densities and having interfacial mass flux. To analyze the interface dynamics from a far field, we develop and apply the general matrix method to rigorously solve the boundary value problem involving the governing equations in the fluid bulk and the boundary conditions at the interface and at the outside boundaries of the domain. We find the fundamental solutions for the linearized system of equations and analyze the interplay of interface stability with flow fields’ structure by directly linking rigorous mathematical attributes to physical observables. We find that the interface is stable when the dynamics conserves the fluxes of mass, momentum, and energy; the stabilization is due to an inertial mechanism causing small oscillations of the interface velocity. In the classic Landau’s dynamics, the postulate of perfect constancy of the interface velocity leads to the development of Landau–Darrieus instability. This destabilization is also linked to the imbalance of the perturbed energy at the interface. The classic Landau’s solution is found to have degeneracy; lifting of the degeneracy may lead to singularity and self-similar dynamics. Our results compare well with traditional theories of combustion and propose new experiments to study the dynamics of the interface and the flow fields in combustible systems. We further conduct reactive molecular dynamics simulations to elucidate the complexity of chemical processes, to study the destabilizing effect of energy fluctuations on the interface stability, and to illustrate the chemistry-induced instabilities. In summary, we identify the extreme sensitivity of the interface dynamics to the interfacial boundary conditions, including the formal properties of fundamental solutions and the qualitative and quantitative properties of the flow fields. This provides new opportunities for studies, diagnostics, and control of multiphase flows in a broad range of processes in nature and technology.

42 ENGINEERING↗

Model Development for Multi-Component Fuel Vaporization and Flash Boiling

The objectives of this project are to improve the multi-component fuel droplet and film vaporization models used in internal combustion engine simulation, and to develop a comprehensive model to predict the characteristics of multi-component flash boiling spray. This work explores two approaches to fuel composition treatment for modeling multi-component fuel vaporization: one based on discretization and surrogates, and the other based on continuous thermodynamic distribution of fuel properties. The experimental data collected for model validation are done under three fuel form factors: droplet, spray, and thin film. The study on sprays also include experimentation under non-flash and flash boiling conditions, a phenomenon that enhances fuel vaporization. The main goals of this work are: Design and develop a multi-component fuel droplet and wall film vaporization model using both discrete and continuous thermodynamics methods. Design and develop an analytical model for multi-component flash boiling. Integrate the multi-component droplet and film model into multi-dimensional engine calculations to predict the fuel vaporization process under engine operation condition. Conduct multi-component droplet and fuel film vaporization experiments in a non-combusting chamber to verify the proposed vaporization models. Characterize flash boiling phenomena of multi-component fuel sprays by optical and laser diagnostic techniques. This report will detail the experimental setup and the numerical basis for developing a model to achieve the main goals listed above. Key features of observed multi-component fuel vaporization will be summarized at the end of each experimental sections, and corresponding model performance evaluation will be presented at the end of each model development section.

33 ADVANCED PROPULSION SYSTEMS↗

Through-Thickness Microstructure Characterization in a Centrifugally Cast Austenitic Stainless Steel Nuclear Reactor Primary Loop Pipe Using Time-of-Flight Neutron Diffraction

The US code of Federal Regulations mandates regular inspection of centrifugally cast austenitic stainless steel pipe, commonly used in primary cooling loops in light-water nuclear power plants. These pipes typically have a wall thickness of ~8 cm. Unfortunately, inspection using conventional ultrasonic techniques is not reliable as the microstructure strongly attenuates ultrasonic waves. Work is ongoing to simulate the behavior of acoustic waves in this microstructure and ultimately develop an acoustic inspection method for reactor inspections. In order to account for elastic anisotropy in the material, the texture in the steel was measured as a function of radial distance though the pipe wall. Experiments were conducted on two 10 × 12.7 × 80 mm radial sections of a cast pipe using neutron diffraction scans of 2 mm slices using the HIPPO time-of-flight neutron diffractometer at the Los Alamos Neutron Science Center (LANSCE, Los Alamos, NM, USA). Strong textures dominated by a small number of austenite grains with their (100) direction aligned in the radial direction of the pipe were observed. ODF analysis indicated that up to 70% of the probed volume was occupied by just three single-grain orientations, consistent with grain sizes of almost 1 cm. Texture and phase fraction of both ferrite and austenite phases were measured along the length of the samples. These results will inform the development of a more robust diagnostic tool for regular inspection of this material.

42 ENGINEERING↗

Engineering a modular 44 Ti/ 44 Sc generator: eluate evaluation in preclinical models and estimation of human radiation dosimetry

Background: 44 Sc/ 47 Sc is an attractive theranostic pair for targeted in vivo positron emission tomographic (PET) imaging and beta-particle treatment of cancer. The 44 Ti/ 44 Sc generator allows daily onsite production of this diagnostic isotope, which may provide an attractive alternative for PET facilities that lack in-house irradiation capabilities. Early animal and patient studies have demonstrated the utility of 44 Sc. In our current study, we built and evaluated a novel clinical-scale 44 Ti/ 44 Sc generator, explored the pharmacokinetic profiles of 44 ScCl 3 , [ 44 Sc]-citrate and [ 44 Sc]-NODAGA (1,4,7-triazacyclononane,1-glutaric acid-4,7-acetic acid) in naïve mice, and estimated the radiation burden of 44 ScCl 3 in humans. Methods: 44 Ti/ 44 Sc (101.2 MBq) in 6 M HCl solution was utilized to assemble a modular ZR resin containing generator. After assembly, 44 Sc was eluted with 0.05 M HCl for further PET imaging and biodistribution studies in female Swiss Webster mice. Based on the biodistribution data, absorbed doses of 44 / 47 ScCl 3 in human adults were calculated for 18 organs and tissues using the IDAC-Dose software. Results: 44 Ti in 6 M HCl was loaded onto the organic resin generator with a yield of 99.97%. After loading and initial stabilization, 44 ScCl 3 was eluted with 0.05 M HCl in typical yields of 82.9 ± 5.3% (N = 16), which was normalized to the estimated generator capacity. Estimated generator capacity was computed based on elution time interval and the total amount of 44 Ti loaded on the generator. Run in forward and reverse directions, the 44 Sc/ 44 Ti ratio from a primary column was significantly improved from 1038 ± 440 to 3557 ± 680 (Bq/Bq) when a secondary, replaceable, ZR resin cartridge was employed at the flow outlet. In vivo imaging and ex vivo distribution studies of the reversible modular generator for 44 ScCl 3 , [ 44 Sc]-citrate and [ 44 Sc]-NODAGA show that free 44 Sc remained in the circulation significantly longer than the chelated 44 Sc. The dose estimation of 44 ScCl 3 reveals that the radiation burden is 0.146 mSv/MBq for a 70 kg adult male and 0.179 mSv/MBq for a 57 kg adult female. Liver, spleen and heart wall will receive the highest absorbed dose: 0.524, 0.502, and 0.303 mGy/MBq, respectively, for the adult male. Conclusions: A clinical-scale 44 Ti/ 44 Sc generator system with a modular design was developed to supply 44 ScCl 3 in 0.05 M HCl, which is suitable for further radiolabeling and in vivo use. Our data demonstrated that free 44 ScCl 3 remained in the circulation for extended periods, which resulted in approximately 10 times greater radiation burden than stably chelated 44 Sc. Stable 44 Sc/ 47 Sc-complexation will be more favorable for in vivo use and for clinical utility.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Optimizing Hydronic Heating for Comfort and Performance in Multifamily Housing

Inefficient control settings in multifamily boilers often lead to substantial energy and cost penalties. To address this, a Fault Detection and Diagnostic (FDD) tool was developed to automate data analysis and identify operational faults such as suboptimal outdoor temperature sensor placement, misconfigured outdoor air reset (OAR) curves, excess boiler cycling, and domestic hot water (DHW) setpoint errors. By comparing pre- and post-implementation periods and applying engineering models, the tool quantifies energy savings and reduces manual analysis time by over 90%. Testing on over 100 monitored sites and a targeted subset of 12 buildings showed an average 11% energy savings from remote optimization; further validation across 19 OAR curve changes confirmed the tool’s accuracy, predicting actual savings within ±5% for most cases. Simple payback can be under three years for many multifamily buildings, though rising hardware, labor, and fuel costs create uncertainties, and decarbonization goals increasingly shift focus to electrification. The FDD tool remains invaluable for optimizing existing boilers, enhancing future electrification measures, and adapting to new technologies by refining building load estimates. In doing so, it supports both near-term efficiency and long-term transitions to low-carbon alternatives, ensuring buildings achieve substantial cost and energy benefits throughout their system lifecycles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Gray-Box Fault Models and Applications for Low-Carbon Emission CO 2 Refrigeration Systems

CO 2 refrigeration systems have attracted more attentions in recent years because of their zero-carbon emission advantages compared with traditional refrigerants. These systems are widely used in certain commercial buildings such as supermarkets. However, very limited energy studies have been done for such refrigeration systems under faults. This study investigated five common faults for supermarket transcritical CO 2 refrigeration systems with display cases. The following major tasks were implemented for this study. (1) Five fault models (gray-box format) regarding the power consumption and supply air temperature were proposed for low- and high-temperature display cases, respectively. The models cover: ice accumulation on evaporator coil, evaporator fan partial failure, expansion valve failure, display door open, and condenser blockage. (2) These fault models were calibrated with field tests, and the modeling accuracies were in good agreement with measurement datasets. (3) The proposed fault models demonstrated more than 90% of fault detection for Fault Detection and Diagnostics (FDD) purposes for both field measurement and simulated data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Python catemis package for DARHT Axis-II Dispenser-Cathode Emissivity and Temperature Analysis

The catemis python package includes the analysis methods used in paper "DARHT Axis-II Dispenser-Cathode Emissivity and Temperature", which was presented at the 2021 Weapons Engineering Symposium and Journal (WESJ) hosted by Los Alamos National Laboratory. The paper (LA-UR-21-25647) and presentation (LA-UR-21-28231) report on a temperature and emissivity model that has been developed and applied to data from diagnostics used to measure the surface temperature of the DARHT Axis-II hot dispenser cathode over more than a decade of operation. The catemis package provides all the methods used in reporting these results along with the data files used to create the plots and tables in the paper. This includes methods for loading and processing FAR spectral pyrometer data along with methods for temperature calibration of cathode images.

Koglin, Jason↗

In-situ optical monitoring of gas turbine blade coatings under operational extreme environments

High temperature material systems consisting of thermal barrier coatings and the underlying superalloys are key to achieving higher gas temperatures which in turn control engine efficiencies and reduce emissions. With engine temperatures in excess of the limits that metallic blades and vanes can endure, advanced monitoring techniques that ensure the integrity and durability of these coatings are paramount to continuous and safe operation. Optical methods have the benefit of being non-invasive and are able to capture data under limited access available for monitoring the hot-section of turbines. Addressing Topic 5 on Advanced Instrumentation, the research and development effort for this project titled “In situ optical monitoring of gas turbine blade coatings under operational extreme environments” was completed by University of Central Florida researchers, including Raghavan (PI) and Ghosh (co-PI). In this project, the research team leveraged intrinsic properties of coatings and rare-earth dopants as active and intelligent “sensors” through their optical properties. The outcomes of this project pave the way for diagnostics of turbine blade coatings, under operating environments, through the development of the sensing thermal barrier coating configurations, calibration and associated instrumentation while ensuring coating integrity and durability goals are concurrently met.

42 ENGINEERING↗

High-Density Implosions on OMEGA and the National Ignition Facility (NIF) (Final FY23 report for the subcontract B656484 (formerly B640112))

This final FY23 report for the subcontract B656484 (formerly B640112) “High-Density Implosions on Omega and the National Ignition Facility (NIF)” summarizes MIT’s support of LLNL experiments at OMEGA and the NIF with nuclear diagnostics, platforms and analysis, and of training PhD students. Overall, the tasks identified as Statement-Of-Work (SOW) items for FY23 were accomplished.

42 ENGINEERING↗

Radioisotope Science and Technology Division FY 2025 Core R&D Summary Report: Competitive Projects, Postdoctoral Researchers, and Student Interns

R&D efforts in support of the Oak Ridge National Laboratory (ORNL) Isotope Program Radioisotope Portfolio are led by the Radioisotope Science and Technology Division (RSTD). In addition to supporting the ORNL Isotope Program Radioisotope Portfolio, RSTD supports a portfolio of research related to fundamental properties of radioisotopes and radioisotope applications, including diagnostic and therapeutic uses of medical radioisotopes, radioisotopes for national security, and the production of 238 Pu for the National Aeronautics and Space Administration (NASA) and US Department of Energy (DOE) Office of Nuclear Energy. RSTD is organized into functional science and engineering groups, with most staff members supporting multiple programs. The goal of this organization is to enable synergy between programs such that R&D advances coming from other programs may provide benefit to the ORNL Isotope Program. R&D within RSTD is focused around addressing five grand challenges, as documented in the strategic plan for the DOE Office of Isotope R&D and Production, or DOE Isotope Program (IP), Radioisotope Production R&D activities at ORNL: 1. Maximizing the scientific output of radioisotope transmutation resources, 2. Maximizing the scientific output of radioisotope processing resources, 3. Minimizing waste and having optimal waste disposition, 4. Focusing on product quality and reliability, and 5. Expanding the use of beneficial isotopes. The ORNL Core R&D program, one of the primary R&D components within the ORNL Isotope Program Radioisotope Portfolio, ranges from benchtop to demonstration activities, with a focus on researching enhanced production techniques, developing emerging isotopes, and developing the talent pipeline for radioisotope science and technology. Projects within the Core R&D Program are led primarily by RSTD staff members. In supporting enhanced production techniques, the Core R&D program presents an opportunity to fund novel R&D that might not be tied to a specific radioisotope product but still presents a high potential for broad applicability in the longer term. In supporting the development of emerging isotopes, the Core R&D program develops high-priority isotopes that are not able to be fully supported through production funds.

07 ISOTOPE AND RADIATION SOURCES↗

Remote Detection of Uranium Using Self-Focusing Intense Femtosecond Laser Pulses

Optical measurement techniques can address certain important challenges associated with nuclear safety and security. Detection of uranium over long distances presents one such challenge that is difficult to realize with traditional ionizing radiation detection, but may benefit from the use of techniques based on intense femtosecond laser pulses. When a high-power laser pulse propagates in air, it experiences collapse and confinement into filaments over an extended distance even without external focusing. In our experiments, we varied the initial pulse chirp to optimize the emission signal from the laser-produced uranium plasma at an extended distance. While the ablation efficiency of filaments formed by self-focusing is known to be significantly lower when compared to filaments produced by external focusing, we show that filaments formed by self-focusing can still generate luminous spectroscopic signatures of uranium detectable within seconds over a 10-m range. The intensity of uranium emission varies periodically with laser chirp, which is attributed to the interplay among self-focusing, defocusing, and multi-filament fragmentation along the beam propagation axis. Grouping of multi-filaments incident on target is found to be correlated with the uranium emission intensity. The results show promise towards long-range detection, advancing the diagnostics and analytical capabilities in ultrafast laser-based spectroscopy of high-Z elements.

42 ENGINEERING↗

Single-shot, double-pulse determination of the detonation energy in nanosecond-laser ablation using the blast model

We demonstrate a novel single-shot method to determine the detonation energy of laser-induced plasma and investigate its performance. This approach can be used in cases where there are significant shot-to-shot variations in ablation conditions, such as laser fluctuations, target inhomogeneity, or multiple filamentation with ultrashort pulses. The Sedov blast model is used to fit two time-delayed shadowgrams measured with a double-pulse laser. We find that the reconstruction of detonation parameters is insensitive to the choice of interpulse delay in double-pulse shadowgraphy. In contrast, the initial assumption of expansion dimensionality has a large impact on the reconstructed detonation energy. The method allows for a reduction in the uncertainties of blast wave energy measurements as a diagnostic technique employed in various laser ablation applications.

42 ENGINEERING↗

Portable Waveguide-Based Optical Biosensor

Rapid, on-site diagnostics allow for timely intervention and response for warfighter support, environmental monitoring, and global health needs. Portable optical biosensors are being widely pursued as a means of achieving fieldable biosensing due to the potential speed and accuracy of optical detection. We recently developed the portable engineered analytic sensor with automated sampling (PEGASUS) with the goal of developing a fieldable, generalizable biosensing platform. Here, we detail the development of PEGASUS’s sensing hardware and use a test-bed system of identical sensing hardware and software to demonstrate detection of a fluorescent conjugate at 1 nM through biotin-streptavidin chemistry.

47 OTHER INSTRUMENTATION↗