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At least 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

What does the future hold for utility electricity efficiency programs?

Here, this study develops projections of future spending and savings from electricity efficiency programs funded by electric utility customers in the United States through 2030 based on three scenarios. Our analysis relies on detailed bottom-up modeling of current state energy efficiency policies, demand-side management and integrated resource plans, and regulatory decisions. The three scenarios represent a range of potential outcomes given the policy environment at the time of the study and uncertainties in the broader economic and state policy environment in each state. We project spending to increase to $8.6 billion in 2030 in the medium scenario, about a 45 percent increase relative to 2016 spending. In the high case, annual spending increases to $11.1 billion in 2030 and remains relatively flat in the low case ($6.8 billion in 2030). Our analysis suggests that electricity efficiency programs funded by utility customers will continue to impact load growth significantly at least through 2030, as savings as a percent of retail sales are forecast at 0.7 percent in the medium scenario and 0.98 percent in the high scenario.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Hybrid AI-ML and FE-based Digital Twin Predictive Modeling Framework for a PWR Coolant System Components: Updates on Multi-Time-Series-3D-Location Dependent Usages Factor Prediction

The long-term operation (LTO) of nuclear power plants (NPP) beyond their original design life of 40 years can lead to more material damage associated with cyclic fatigue under thermal-mechanical loading cycles and associated long-term exposure of reactor material to the deleterious reactor-coolant environments. However, under this LTO condition, the reactor components can still safely operate but may require more frequent Nondestructive Evaluation (NDE) of reactor components. Requiring frequent NDE inspections may lead to frequent NPP shutdowns which can lead to power outages and additional NDE inspection cost-related economic loss. The economic loss can be minimized by reducing uncertainty in life estimation of safety-critical pressure boundary components and by implementing a more digital approach such as using upcoming digital-twin (DT) technology for predicting the structural states (e.g., time and location dependent inside/outside thickness temperature, stress, strain, plastic deformation, etc.) and associated fatigue life of a component in real time. The DT framework is based on limited experimental data, Artificial-intelligence (AI)-Machine-Learning (ML) and multiphysics-computationalmechanics such as finite element- (FE) based models. Given the real-time thermal-hydraulic process measurements from several existing plant sensors, the overall goal of the DT framework is to predict the cumulative usages factors or equivalent fatigue lives in real time and at any random 3D location of the components. This includes inaccessible locations such as inside the thickness or location of a component. This prediction can be at thousands to millions of 3D point clouds or locations like conventional FE-based models, but without running an FE model in real time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2016

Probabilistic Modeling Of Ocular Biomechanics In VIIP: Risk Stratification

Visual Impairment and Intracranial Pressure (VIIP) syndrome is a major health concern for long-duration space missions. Currently, it is thought that a cephalad fluid shift in microgravity causes elevated intracranial pressure (ICP) that is transmitted along the optic nerve sheath (ONS). We hypothesize that this in turn leads to alteration and remodeling of connective tissue in the posterior eye which impacts vision. Finite element (FE) analysis is a powerful tool for examining the effects of mechanical loads in complex geometries. Our goal is to build a FE analysis framework to understand the response of the lamina cribrosa and optic nerve head to elevations in ICP in VIIP. To simulate the effects of different pressures on tissues in the posterior eye, we developed a geometric model of the posterior eye and optic nerve sheath and used a Latin hypercubepartial rank correlation coef-ficient (LHSPRCC) approach to assess the influence of uncertainty in our input parameters (i.e. pressures and material properties) on the peak strains within the retina, lamina cribrosa and optic nerve. The LHSPRCC approach was repeated for three relevant ICP ranges, corresponding to upright and supine posture on earth, and microgravity [1]. At each ICP condition we used intraocular pressure (IOP) and mean arterial pressure (MAP) measurements of in-flight astronauts provided by Lifetime Surveillance of Astronaut Health Program, NASA Johnson Space Center. The lamina cribrosa, optic nerve, retinal vessel and retina were modeled as linear-elastic materials, while other tissues were modeled as a Mooney-Rivlin solid (representing ground substance, stiffness parameter c1) with embedded collagen fibers (stiffness parameters c3, c4 and c5). Geometry creationmesh generation was done in Gmsh [2], while FEBio was used for all FE simulations [3]. The LHSPRCC approach resulted in correlation coefficients in the range of 1. To assess the relative influence of the uncertainty in an input parameter on the peak strains, we ranked and then normalized these coefficients, considering that normalized values 0.5 implied a substantial influence on the range of the peak strains in the optic nerve head (ONH). IOP and ICP were found to have a major influence on the peak strains in the ONH, as did optic nerve and LC stiffness. Interestingly, the stiffness of the sclera far from the scleral canal did not have a large influence on peak strains in ONH tissues; however, the collagen fiber stiffness in the peripapillary sclera and annular ring both influenced the peak strains within the ONH. We have created a physiologically relevant model that incorporated collagen fibers to study the effects of elevated ICP. Elevated ICP resulted in strains in the optic nerve that are not predicted to occur on earth: the upright or supine conditions. We found that IOP, ICP, lamina cribrosa stiffness and optic nerve stiffness had the highest association with these extreme strains in the ONH. These extreme strains may activate mechanosensitive cells that induce tissue remodeling and are a risk factor for the development of VIIP.

biomechanics↗
NASA NTRS2014

Assessing the Risk of Crew Injury Due to Dynamic Loads During Spaceflight

Spaceflight requires tremendous amounts of energy to achieve Earth orbit and to attain escape velocity for interplanetary missions. Although the majority of the energy is managed in such a way as to limit the accelerations on the crew, several mission phases may result in crew exposure to dynamic loads. In the automotive industry, risk of serious injury can be tolerated because the probability of a crash is remote each time a person enters a vehicle, resulting in a low total risk of injury. For spaceflight, the level of acceptable injury risk must be lower to achieve a low total risk of injury because the dynamic loads are expected on each flight. To mitigate the risk of injury due to dynamic loads, the NASA Human Research Program has developed a research plan to inform the knowledge gaps and develop relevant tools for assessing injury risk. The risk of injury due to dynamic loads can be further subdivided into extrinsic and intrinsic risk factors. Extrinsic risk factors include the vehicle dynamic profile, seat and restraint design, and spacesuit design. Human tolerance to loads varies considerably depending on the direction, amplitude, and rise-time of acceleration therefore the orientation of the body to the dynamic vector is critical to determining crew risk of injury. Although a particular vehicle dynamic profile may be safe for a particular design, the seat, restraint, and suit designs can affect the risk of injury due to localized effects. In addition, characteristics intrinsic to the crewmember may also contribute to the risk of injury, such as crewmember sex, age, anthropometry, and deconditioning due to spaceflight, and each astronaut may have a different risk profile because of these factors. The purpose of the research plan is to address any knowledge gaps in the risk factors to mitigate injury risk. Methods for assessing injury risk have been well documented in other analogous industries and include human volunteer testing, human exposure to dynamic environments, post-mortem human subject (PMHS) testing, animal testing, anthropomorphic test devices (ATD), dynamic models of the human, numerical models of ATDs, and numerical models of the human. Each has inherent strengths and limitations. For example, human volunteer testing is advantageous because a population can be selected that is similar to the astronaut corps; however, because of the inherent ethical limitations, only sub-injurious conditions can be tested. PMHSs can be tested in a variety of conditions including injurious levels, but the responses are not completely analogous to living human subjects. In addition, it is exceedingly difficult to select a PMHS population that is similar to the astronaut corps. ATDs are currently widely used in the automotive industry and military because they are highly repeatable and durable. Unfortunately, because they are mechanical models of the human body, the biofidelity of the responses are limited to dynamic conditions used to validate the ATD. Numerical models of the ATD, in addition to the strengths and limitations for ATDs, are easy to use for a variety of designs before a design is fabricated, but also have additional limitations for ATDs, are easy to use for a variety of designs before a design is fabricated, but also have additional uncertainty. Dynamic models are simple and easy to use, but do not account for localized effects of the seat and suit. Finally, numerical models of the human have the potential to have the most advantages; however, the current models are not validated for the conditions expected during spaceflight. To properly assess spaceflight conditions with numerical human models, human data would be needed to optimize the model responses for those conditions. Using the appropriate assessment method with the knowledge gained for each risk factor, an appropriate approach for mitigating the risk of injury due to dynamic loads can be developed ensuring crew safety in future NASA vehicles.

Somers, J. T.↗
DOE OSTI2021

Cookoff of Powdered and Pressed Explosives using a Micromechanics Pressurization Model

Cookoff experiments of powdered and pressed TATB-based plastic bonded explosives (PBXs) have been modeled using a pressure-dependent universal cookoff model (UCM) in combination with a micromechanics pressurization (MMP) model described in a companion paper. The MMP model is based on the accumulation of decomposition gases at nucleation sites that load the surrounding TATB crystals and binder. This is the first cookoff model to use an analytical mechanics solution for compressibility and thermal expansion to describe internal pressurization caused by both temperature and decomposition occurring within closed-pore explosives. This approach produces more accurate predictions of ignition time and pressurization within high-density explosives than simple equation-of-state models. The current paper gives details of the reaction chemistry, model parameters, predicted uncertainty, and validation using experiments from multiple laboratories with errors less than 6 %. The UCM/MMP model framework gives more accurate thermal ignition predictions for high density explosives that are initially impermeable to decomposition gases.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Economic Analysis of an Electric Thermal Energy Storage System Using Solid Particles for Grid Electricity Storage

As renewable power generation becomes the mainstream new-built energy source, energy storage will become an indispensable need to complement the uncertainty of renewable resources to firm the power supply. When phasing out fossil-fuel power plants to meet the carbon neutral utility target in the midcentury around the world, large capacity of energy storage will be needed to provide reliable grid power. The renewable power integration with storage can support future carbon-free utility and has several significant impacts including increasing the value of renewable generation to the grid, improving the peak-load response, and balancing the electricity supply and demand. Long-duration energy storage (10–100 hours duration) can potentially complement the reduction of fossil-fuel baseload generation that otherwise would risk grid security when a large portion of grid power comes from variable renewable sources. Current energy storage methods based on pumped storage hydropower or batteries have many limitations. Thermal energy storage (TES) has unique advantages in scale and siting flexibility to provide grid-scale storage capacity. A particle-based TES system has promising cost and performance for the future growing energy storage needs. This paper introduces the system and components required for the particle TES to be technically and economically competitive. A technoeconomic analysis based on preliminary component designs and performance shows that the particle TES integrated with an efficient air-Brayton combined cycle power system can provide power for several days by low-cost, high-performance storage cycles. It addresses grid storage needs by enabling large-scale grid integration of intermittent renewables like wind and solar, thereby increasing their grid value. The design specifications and cost estimations of major components in a commercial scale system are presented in this paper. The cost model provides insights for further development and cost comparison with competing technologies.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2021

Economic Analysis of a Novel Thermal Energy Storage System Using Solid Particles for Grid Electricity Storage: Preprint

As renewable power generation becomes the mainstream new-built energy source, energy storage will become an indispensable need to complement the uncertainty of renewable resources to firm the power supply. When phasing out fossil-fuel power plants to meet the carbon neutral utility target in the midcentury around the world, large capacity of energy storage will be needed to provide reliable grid power. The integration of renewable power and storage to support future carbon-free utility has several significant and positive impacts including expanding the renewable generation into the grid, improving the peak-load response, and balancing the electricity supply and demand. Long-duration energy storage (10–100 hours duration) can potentially complement the reduction of fossil-fuel baseload generation that otherwise would risk grid security when a large portion of grid power comes from variable renewable sources. Current energy storage methods based on pumped storage hydropower or batteries have many limitations. Thermal energy storage (TES) has unique advantages in scale and siting flexibility to provide grid-scale storage capacity. A particle-based TES system has promising cost and performance for the future growing energy storage needs. This paper introduces the system and components required for the particle TES to be technically and economically competitive. A technoeconomic analysis based on preliminary component designs and performance shows that the particle TES integrated with an efficient air-Brayton combined cycle power system can provide power for several days by low-cost, high-performance storage cycles. It addresses grid storage needs by enabling large-scale grid integration of intermittent renewables like wind and solar, thereby increasing their grid value. The design specifications and cost estimations of major components in a commercial scale system are presented in this paper. The cost model provides insights for further development and cost comparison with competing technologies.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2022

Insights into Methodologies and Operational Details of Resource Adequacy Assessment: A Case Study with Application to a Broader Flexibility Framework

Assessing and maintaining resource adequacy (RA) is a core pillar of power systems. However, recent changes in the physical makeup of these systems and the conditions under which these systems must operate have yielded a renewed interest in the methods, metrics, and assumptions that underpin RA assessments. In this paper, we systematically explore a wide range of RA modeling dimensions, including: the objective function and level of operational detail in the underlying model formulation; the quantity (look-ahead) and quality (accuracy) of data that is available for making operational decisions within those models; and the physical configuration of solar photovoltaics (PV) with battery storage hybrid resources. We apply a set of probabilistic RA tools and production cost modeling tools to a realistic test system based loosely on a future Electric Reliability Council of Texas power system dominated by solar PV resources. Under the assumptions of our system and models, we find that multi-stage probabilistic assessments may provide a more robust evaluation of RA by capturing a wider range of operational and system interactions, but this comes at a computational cost of 1-2 orders of magnitude longer run time depending on the specific configuration. In addition, the information on thermal generator availability impacts RA performance by an order of magnitude more than solar resource forecasts, which is driven by the comparatively larger magnitude of thermal outages than solar forecast errors within our test system. Lastly, the flexibility provided by hybrid and other resources can help reduce system load-shedding event frequencies and enable the system to be more robust to inaccurate forecast information, and alternative hybrid inverter sizes can impact RA levels by 1-2 orders of magnitude. Our results point to the importance of a broader flexibility framework to describe the interaction between (1) flexibility "supply" from both physical resource capabilities and operational constraints considered in the modeling, and (2) flexibility "demand" from forecast errors, thermal generator outages, and other sources of uncertainty, as well as their RA impacts. Results are likely sensitive to the system buildout explored; future work could consider additional system configurations and conditions.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗
NASA NTRS1998

Ultrasonic Attenuation Results of Thermoplastic Resin Composites Undergoing Thermal and Fatigue Loading

As part of an effort to obtain the required information about new composites for aviation use, materials and NDE researchers at NASA are jointly performing mechanical and NDE measurements on new composite materials. The materials testing laboratory at NASA is equipped with environmental chambers mounted on load frames that can expose composite materials to thermal and loading cycles representative of flight protocols. Applying both temperature and load simultaneously will help to highlight temperature and load interactions during the aging of these composite materials. This report highlights our initial ultrasonic attenuation results from thermoplastic composite samples that have undergone over 4000 flight cycles to date. Ultrasonic attenuation measurements are a standard method used to assess the effects of material degradation. Recently, researchers have shown that they could obtain adequate contrast in the evaluation of thermal degradation in thermoplastic composites by using frequencies of ultrasound on the order of 24 MHz. In this study, we address the relationship of attenuation measured at lower frequencies in thermoplastic composites undergoing both thermal and mechanical loading. We also compare these thermoplastic results with some data from thermoset composites undergoing similar protocols. The composite s attenuation is reported as the slope of attenuation with respect to frequency, defined as b = Da(f)/Df. The slope of attenuation is an attractive parameter since it is quantitative, yet does not require interface corrections like conventional quantitative attenuation measurements. This latter feature is a consequence of the assumption that interface correction terms are frequency independent. Uncertainty in those correction terms can compromise the value of conventional quantitative attenuation data. Furthermore, the slope of the attenuation more directly utilizes the bandwidth information and in addition, the bandwidth can be adjusted in the post processing stage to compensate for the loss of dynamic range of the signal as the composites age.

Madaras, Eric I.↗
DOE OSTI2026

Examining the Impacts of Microphysical-Dynamical Feedbacks on Convective Clouds in Different Aerosol Environments Using Enhanced Observational and Modeling Strategies

This project investigated how microphysical–dynamical feedbacks influence deep convective clouds across a range of aerosol conditions, storm lifecycles, and meteorological regimes, and how these sensitivities depend on the modeling framework used to represent convection and microphysics. Using the Aerosol, Cloud, Precipitation, and Climate (ACPC) Working Group model intercomparison simulations of isolated deep convection in the Houston region, we found a robust warm-phase aerosol response in most cloud-resolving models. Increased aerosol loading tended to suppress warm-rain production, increase cloud water, and reduce surface rainfall and near-surface evaporation. These impacts were typically strongest early in the convective lifecycle, with the largest aerosol-driven differences occurring during the first half of storm evolution. The ice-phase response, on the other hand, varied widely across modeling frameworks, and differed in sign, timing, and vertical structure. Ice microphysical pathways and parameterizations are therefore leading sources of uncertainty in aerosol–deep convection interactions. Theoretical analyses further suggested that aerosol-driven invigoration through cold-phase processes was much weaker than previously hypothesized for cold-based storms, and in warm-based storms could even reduce updraft strength. These results imply that any invigoration signal is more likely linked to warm-phase processes and peaks early in storm development.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

Pulse Detonation Rocket MHD Power Experiment

A pulse detonation research engine (MSFC (Marshall Space Flight Center) Model PDRE (Pulse Detonation Rocket Engine) G-2) has been developed for the purpose of examining integrated propulsion and magnetohydrodynamic power generation applications. The engine is based on a rectangular cross-section tube coupled to a converging-diverging nozzle, which is in turn attached to a segmented Faraday channel. As part of the shakedown testing activity, the pressure wave was interrogated along the length of the engine while running on hydrogen/oxygen propellants. Rapid transition to detonation wave propagation was insured through the use of a short Schelkin spiral near the head of the engine. The measured detonation wave velocities were in excess of 2500 m/s in agreement with the theoretical C-J velocity. The engine was first tested in a straight tube configuration without a nozzle, and the time resolved thrust was measured simultaneously with the head-end pressure. Similar measurements were made with the converging-diverging nozzle attached. The time correlation of the thrust and head-end pressure data was found to be excellent. The major purpose of the converging-diverging nozzle was to configure the engine for driving an MHD generator for the direct production of electrical power. Additional tests were therefore necessary in which seed (cesium-hydroxide dissolved in methanol) was directly injected into the engine as a spray. The exhaust plume was then interrogated with a microwave interferometer in an attempt to characterize the plasma conditions, and emission spectroscopy measurements were also acquired. Data reduction efforts indicate that the plasma exhaust is very highly ionized, although there is some uncertainty at this time as to the relative abundance of negative OH ions. The emission spectroscopy data provided some indication of the species in the exhaust as well as a measurement of temperature. A 24-electrode-pair segmented Faraday channel and 0.6 Tesla permanent magnet assembly were then installed on Marshall Space Flight Center's (MSFC's) rectangular channel pulse detonation research engine. Magnetohydrodynamic (MHD) electrical power extraction experiments were carried out for a range of load impedances in which cesium hydroxide seed (dissolved in methanol) was sprayed into the gaseous oxygen/hydrogen propellants. Positive power extraction was obtained, but preliminary analysis of the data indicated that the plasma electrical conductivity is lower than anticipated and the near-electrode voltage drop is not negligible. It is believed that the electrical conductivity is reduced due to a large population of negative OH ions. This occurs because OH has a strong affinity for capturing free electrons. The effect of near-electrode voltage drop is associated with the high surface-to-volume ratio of the channel (1-inch by 1-inch cross-section) where surface effects play a dominant role. As usual for MHD devices, higher performance will require larger scale devices. Overall, the gathered data is extremely valuable from the standpoint of understanding plasma behavior and for developing empirical scaling laws.

Litchford, Ron J.↗
DOE OSTI2025

Cost-Benefit Analysis of Electricity Resilience Projects: State of the Art and Gap Analysis

Utilities and regulators must weigh the benefits of electricity resilience projects against their costs, which would be passed on to customers. Cost-benefit analysis (CBA) is an appropriate method for assessing this tradeoff. Here, in this paper we review the literature on CBA of electricity resilience projects and analyze gaps in the available methods and tools. The costs of resilience projects are typically straightforward to estimate but their benefits — particularly the avoided costs of power interruptions — are complex to quantify and monetize. A common perception among practitioners is that current CBA tools are not sufficiently mature to be adopted into real-world practice. We propose an electricity resilience CBA framework consisting of several elements: risks, physical impacts, power interruptions, economic impacts, and resilience projects. While methods for some elements are well-developed, there is a need for novel approaches to value avoided power interruptions, integrate multiple risks and benefit streams, and incorporate uncertainty.

Cost-benefit analysis↗
DOE OSTI2022

Stochastic Strategic Participation of Active Distribution Networks With High-Penetration DERs in Wholesale Electricity Markets

With the increasing penetration of distributed energy resources (DERs), traditional distribution networks as load-serving entities in wholesale electricity markets, now evolve towards active distribution networks (ADNs) which can proactively participate in wholesale markets by optimally controlling the DERs in their networks. A stochastic bilevel optimization model is proposed in this paper for the strategic participation of ADNs and DERs to provide energy and grid services in wholesale electricity markets. The bilevel optimization model can capture the interactions between the ADN and the wholesale energy and ancillary service markets, considering the uncertainties of DERs in the ADN. In the upper-level model, the ADN makes optimal decisions on energy and reserve bidding considering the availability, uncertainties, and flexibility of DERs. The joint energy and reserve market-clearing of the independent system operator (ISO) is modeled as the lower-level problem. Using strong duality theory and Karush-Kuhn Tucker (KKT) conditions, the proposed bilevel optimization problem is reformulated as mathematical programming with equilibrium constraints (MPEC) problem and further converted into a computationally-solvable mixed-integer second-order-cone programming (MISOCP) model. The simulation results demonstrate the effectiveness of the model and the interactions between an ADN and wholesale electricity markets.

active distribution network↗
NASA NTRS2023

Efficient Two-Way Coupled Analysis of Steady-State Particle-Laden Hypersonic Flows

A direct solution approach for surface erosion in particle-laden hypersonic flows is extended for use in low-cost two-way coupled solutions of dilute gas-particle flows. The Trajectory Control Volume method, which uses a sparse set of probe particles to predict surface erosion distributions on general vehicles, is reformulated for the solution of source terms by mean trajectory subdivision and computing a flux differencing. The approach is verified successfully against a boundary layer solution and shown to agree well with experimental measurements. A representative Mars entry case, with conditions and geometry based on the ExoMars Schiaparelli capsule, is solved with the approach to study the impact of two-way coupling on surface heating and erosion. Results indicate that for realistic loading conditions, heating is largely unmodified compared to one-way coupled results at peak heating trajectory conditions, and no measureable difference is observed in the surface erosion rate. At exaggerated loading conditions high enough to observe coupling effects, the worst case collisional heating can increase heating by up to 60%.

Particle Laden Flow↗
DOE OSTI2020

A Fast Flexibility-Driven Generation Portfolio Planning Method for Sustainable Power Systems

We are witnessing an acceleration in the uptake of renewable energy in power systems. Because of the associated variability and uncertainty of renewables, power systems need to have an adequate supply of flexibility to allow for suitable management of short-term operations. So far most of the work in this area has neglected how flexibility needs associated with renewables are fulfilled as part of dispatchable generation capital investments decisions. To address this challenge, we propose an approach to plan the dispatchable generation mix of a power system as needed to counteract variability and uncertainty associated with significant shares of variable renewable generation. The approach exploits the linear time-invariant feature of variable generation variability using historical phase planes of capacity (in MW) and ramp (in MW/min) to bridge the gap between long-term capacity planning and short-term intra-hour flexibility needs. This approach is much more computationally tractable than other proposals, while also being able to capture adequately short-term operational features like ramping and net load variability. Numerical tests are performed on realistic datasets to substantiate the effectiveness of the approach.

bulk power system planning↗
NASA NTRS1988

Probabilistic system identification in the time domain

The objective of system identification is to determine reliable dynamical models of a structure by systematically using its measured excitation and response. It brings together in an integrated fashion, experimental, analytical, and computational techniques in structural dynamics. Areas of application for system identification include the following: (1) Model Evaluation--assessing assumptions (linearity and equivalent viscous damping) and techniques (finite-element modeling) used to construct theoretical models of a structure; (2) Model Improvement--updating of a theoretical model to enable more accurate response predictions for possible future loads on the structure, or for control of the structure; (3) Empirical Modelling--developing empirical relationships (nonlinear models) or empirical parameter values (modal damping) because the present state of the art does not provide theoretical results; and (4) Damage Detection and Assessment--continual or episodic updating of a structural model through vibration monitoring to detect and locate any structural damage. It can be argued that since the construction or modification of models using test data is subject to inherent uncertainties, the above problems should be properly treated within a Bayesian probabilistic framework. Such a methodology is presented which allows the precision of the estimates of the model parameters to be computed. It also leads to a guiding principle in applications. Namely, when selecting a single model from a given class of models, one should take the most probable model in the class based on the experimental data. Practical applications of this principle are given which are based on the utilization of measured seismic motions in large civil structures. Examples include the application of a computer program MODE-ID to identify modal properties directly from seismic excitation and response time histories from a nine-story steel-frame building at JPL and from a freeway overpass bridge.

Beck, James L.↗
DOE OSTI2022

High-Fuel Loading Ignition Delay Time Characterization of Hydrogen/Natural Gas/Ammonia at Gas Turbine-Relevant Conditions Inside a High-Pressure Shock Tube

Abstract This study explores the combustion characterization of high-fuel percentage, air-diluted mixtures of H2 mixed with natural gas (NG) as well as mixtures of H2 and NH3 at temperatures and pressures relevant to turbine operating conditions (20–30 bar, 1000–1500 K). Lower temperatures (below 1070 K) exhibit preignition characteristics due to non-homogeneity. An attempt to mitigate these occurrences at high pressures is investigated using the constrained reaction volume (CRV) stage-filling technique. Due to the need to further refine the facility CRV stage-filling uncertainty, only higher temperature data will be interpreted at this time. The test conditions in this study closely replicate the temperatures, pressures, and mixtures that would be seen in hydrogen-powered gas turbines, making it the first to explore such conditions. The experimental IDTs were compared against the current state-of-the-art chemical kinetic models for mechanism validation. The current work will advance H2-powered turbines and aims to determine the optimum molecular ratio of H2 when mixed with natural gas.

Pierro, Michael↗
DOE OSTI2025

A Probabilistic Reasoner Based on Bayes Risk for Damage Detection in Structural Systems

Structural health monitoring (SHM) systems are used to inform operation of structural systems subject to loads and environments that may affect their integrity. SHM systems rely on continuous monitoring of the structure to determine its health state. These systems are often coupled with a model of the deployed structure to determine the consequences of changes in the system by forecasting the response to future states. These models, which may be thought of as digital twins, need to be updated to reflect the latest state of the structural system. This work makes use of an uncertainty-aware machine learning model that enforces distance preservation of the original input space to determine deviations from the training data input space distributions. This workflow enables domain shift detection to determine whether damage is present in the structure. The uncertainty metrics generated by this network are then used in a Bayes risk framework to design an optimal damage detector given cost and risk considerations. The approach is demonstrated on a computational example with simulated damage.

Najera-Flores, David [ATA Engineering, Inc.]↗