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At least 451 records · Page 25

Development of a thermal storage module using modified anhydrous sodium hydroxide

The laboratory scale testing of a modified anhydrous NaOH latent heat storage concept for small solar thermal power systems such as total energy systems utilizing organic Rankine systems is discussed. A diagnostic test on the thermal energy storage module and an investigation of alternative heat transfer fluids and heat exchange concepts are specifically addressed. A previously developed computer simulation model is modified to predict the performance of the module in a solar total energy system environment. In addition, the computer model is expanded to investigate parametrically the incorporation of a second heat exchange inside the module which will vaporize and superheat the Rankine cycle power fluid.

Rice, R. E.↗

Rocket injector single element characterization at the Marshall Space Flight Center

The paper describes three experimental facilities which are being developed at NASA's Marshall Space Flight Center (MSFC) for rocket injector cold-flow characterization. The first of these is an already operational cold-flow ambient-backpressure facility, which uses water and air to simulate LOX and gaseous hydrogen, respectively; the facility can be used to obtain discharge coefficients, to measure flow uniformity, and to develop diagnostic techniques for use in the high-backpressure cold-flow chamber that is being currently developed at MSFC. The second is a cold-flow acrylic model facility to be used for evaluating the effect of changes in the internal flow geometry on the performance and combustion stability characteristics of a swirl coaxial LOX post. The third is a high-pressure cold-flow facility to be used for the characterization of the injector elements' performance; a specific application is to determine the effect of swirl elements on the temperature striations in the SSME preburners.

Hutt, J.↗

Aircraft Engine On-Line Diagnostics Through Dual-Channel Sensor Measurements: Development of an Enhanced System

In this paper, an enhanced on-line diagnostic system which utilizes dual-channel sensor measurements is developed for the aircraft engine application. The enhanced system is composed of a nonlinear on-board engine model (NOBEM), the hybrid Kalman filter (HKF) algorithm, and fault detection and isolation (FDI) logic. The NOBEM provides the analytical third channel against which the dual-channel measurements are compared. The NOBEM is further utilized as part of the HKF algorithm which estimates measured engine parameters. Engine parameters obtained from the dual-channel measurements, the NOBEM, and the HKF are compared against each other. When the discrepancy among the signals exceeds a tolerance level, the FDI logic determines the cause of discrepancy. Through this approach, the enhanced system achieves the following objectives: 1) anomaly detection, 2) component fault detection, and 3) sensor fault detection and isolation. The performance of the enhanced system is evaluated in a simulation environment using faults in sensors and components, and it is compared to an existing baseline system.

Kobayashi, Takahisa↗

Digital twin framework for PIP-II linac: AI-driven multi-scale modeling from ion source to 800 MeV

The PIP-II superconducting linac at Fermilab is designed to deliver multi-megawatt proton beams for neutrino physics and other high-intensity applications. To expedite commissioning and enhance operational reliability, we have developed an EPICS-based data flow framework that seamlessly integrates digital twins (DT) with physical twins (PT). These digital twins comprise high-fidelity beam dynamics models or data-driven surrogate models connected to their physical counterparts through real-time diagnostics and advanced machine-learning algorithms.Central to this framework is Linac_Gen, an accelerated simulation tool that incorporates convolutional neural networks, random forests, and genetic algorithms to provide up to a tenfold speedup in optimizing the accelerator geometry model. An EPICS translator layer ensures interoperability by efficiently mapping lattice parameters across diverse simulation platforms.Our EPICS-based framework supports multiple operational modes—monitoring, passive learning, closed-loop control, and online learning—covering the entire machine lifecycle. By leveraging HPC resources and multi-objective optimization techniques, the digital twin enables adaptive trajectory correction, real-time fault detection, and predictive modeling of beam stability. This comprehensive approach paves the way for robust, high-intensity operation and data-driven accelerator R&D at Fermilab.

Pathak, Abhishek [Fermilab]↗

Transport of Passive Tracers in Baroclinic Wave Life Cycles

The transport of passive tracers in idealized baroclinic wave life cycles is studied using output from the National Center for Atmospheric Research Community Climate Model (CCM2). Two life cycles, LCn and LCs, are simulated, starting with baroclinically unstable initial conditions similar to those used by Thorncroft et al. in their study of two life cycle paradigms. The two life cycles LCn and LCs have different initial horizontal wind shear structures that result in distinctive nonlinear development. In terms of potential vorticity-potential temperature (PV-theta) diagnostics, the LCn case is characterized by thinning troughs that are advected anti-cyclonically and equatorward, while the LCs case has broadening troughs that wrap up cyclonically and poleward. Four idealized passive tracers are included in the model to be advected by the semi-Lagrangian transport scheme of the CCM2, and their evolutions are investigated throughout the life cycles. Tracer budgets are analyzed in terms of the transformed Eulerian mean constituent transport formalism in pressure coordinates and also in isentropic coordinates. Results for both LCn and LCs show transport that is downgradient with respect to the background structure of the tracer field, but with a characteristic spatial structure that maximizes in the middle to high latitudes. For the idealized tropospheric tracers in this study, this represents a net upward and poleward transport that enhances concentrations at high latitudes. These results vary little with the initial distribution of the constituent field. The time tendency of the tracer is influenced most strongly by the eddy flux term. with the largest transport occurring during the nonlinear growth stage of the life cycle. The authors also study the transport of a lower-stratospheric tracer, to examine stratosphere-troposphere exchange for baroclinic waves.

Stone, Elizabeth M.↗

Stress Birth and Death: Disruptive Computational Mechanics and Novel Diagnostics for Fluid-to-Solid Transitions

Many materials of interest to Sandia transition from fluid to solid or have regions of both phases coexisting simultaneously. Currently there are, unfortunately, no material models that can accurately predict this material response. This is relevant to applications that "birth stress" related to geoscience, nuclear safety, manufacturing, energy production and bioscience. Accurately capturing solidification and residual stress enables fully predictive simulations of the evolving front shape or final product. Accurately resolving flow of proppants or blood could reduce environmental impact or lead to better treatments for heart attacks, thrombosis, or aneurism. We will address a science question in this proposal: When does residual stress develop during the critical transition from liquid to solid and how does it affect material deformation? Our hypothesis is that these early phases of stress development are critical to predictive simulation of material performance, net shape, and aging. In this project, we use advanced constitutive models with yield stress to represent both fluid and solid behavior simultaneously. The report provides an abbreviated description of the results from our LDRD "Stress Birth and Death: Disruptive Computational Mechanics and Novel Diagnostics for Fluid-to-Solid Transitions," since we have written four papers that document the work in detail and which we reference. We give highlights of the work and describe the gravitationally driven flow visualization experiment on a model yield stress fluid, Carbopol, at various concentrations and flow rates. We were able to collapse the data on a single master curve by showing it was self-similar. We also describe the Carbopol rheology and the constitutive equations of interest including the Bingham-Carreau-Yasuda model, the Saramito model, and the HB-Saramito model including parameter estimation for the shear and oscillatory rheology. We present several computational models including the 3D moving mesh simulations of both the Saramito models and Bingham-Carreau-Yasuda (BCY) model. We also show results from the BCY model using a 3D level set method and two different ways of handling reduced order Hele-Shaw modeling for generalized Newtonian fluids. We present some first ever two-dimensional results for the modified Jeffries Kamani-Donley-Rogers constitutive equation developed during this project. We include some recent results with a successful Saramito-level set coupling that allows us to tackle problems with complex geometries like mold filling in a thin gap with an obstacle, without the need for remeshing or remapping. We report on some experiments for curing systems where fluorescent particles are used to track material flow. These experiments were carried out in an oven on Sylgard 184 as a model polymerizing system. We conclude the report with a summary of accomplishments and some thoughts on follow-on work.

36 MATERIALS SCIENCE↗

Mars Global Surveyor: Aerobraking and Observations Support Using a Mars Global Circulation Model

This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Center and San Jose State University, Department of Meteorology. Using a global atmospheric circulation model for Mars, the focus of this JRI has been to provide support for the Mars Global Surveyor (MGS) spacecraft aerobraking activities and interpretation guidance of preliminary observations. The primary atmospheric model applied in this investigation has been a high-top version of the NASA Ames Mars general circulation model (MGCM). Comparisons with an atmospheric model designed primarily for engineering purposes (Mars-GRAM) has also been carried out. From a suite of MGCM simulations, we have assessed plausible spatial and temporal variability in atmospheric density at high altitudes (e.g., 70-110 km) for seasonal dates and locations during Phase I aerobraking. Diagnostic tools have been developed to analyze circulation fields from the MGCM simulations, and these tools have been applied in the creation of a Mars climate catalogue database. Throughout Phase I aerobraking activities, analysis products have been provided to the MGS aerobraking atmospheric advisory group (AAG). Analyses of circulation variability at the coupling level between the MGCM and a Mars thermospheric global circulation model (MTGCM) has also been assessed. Finally, using a quasi-geostrophic dynamical formulation with the MGCM simulations, diagnosis of breaking planetary (Rossby) waves in Mars' middle atmosphere has been carried out. Titles of papers presented at scientific workshops and seminars, and a publication in the scientific literature are provided.

Hollingsworth, Jeffery L.↗

Mars Global Surveyor: Aerobraking and Observations Support Using a Mars Global Circulation Model

This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Center and San Jose State University, Department of Meteorology. Using a global atmospheric circulation model for Mars, the focus of this JRI has been to provide support for the Mars Global Surveyor (MGS) spacecraft aerobraking activities and interpretation guidance of preliminary observations. ne primary atmospheric model applied in this investigation has been a high-top version of the NASA Ames Mars general circulation model (MGCM). Comparisons with an atmospheric model designed primarily for engineering purposes (Mars-GRAM) has also been carried out. From a suite of MGCM simulations, we have assessed plausible spatial and temporal variability in atmospheric density at high altitudes (e.g., 70-110 km) for seasonal dates and locations during Phase 1 aerobraking. Diagnostic tools have been developed to analyze circulation fields from the MGCM simulations, and these tools have been applied in the creation of a Mars climate catalogue database. Throughout Phase 1 aerobraking activities, analysis products have been provided to the MGS aerobraking atmospheric advisory group (AAG). Analyses of circulation variability at the coupling level between the MGCM and a Mars thermospheric global circulation model (MTGCM) has also been assessed. Finally, using a quasi-geostrophic dynamical formulation with the MGCM simulations, diagnosis of breaking planetary (Rossby) waves in Mars' middle atmosphere has been carried out. Titles of papers presented at scientific workshops and seminars, and a publication in the scientific literature are provided.

Hollingsworth, Jeffery L.↗

Mars Global Surveyor: Aerobraking and Observations Support Using a Mars Global Circulation Model

This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Center and San Jose State University, Department of Meteorology. Using a global atmospheric circulation model for Mars, the focus of this JRI has been to provide support for the Mars Global Surveyor (MGS) spacecraft aerobraking activities and interpretation guidance of preliminary observations. The primary atmospheric model applied in this investigation has been a high-top version of the NASA Ames Mars general circulation model (MGCM). Comparisons with an atmospheric model designed primarily for engineering purposes (Mars-GRAM) has also been carried out. From a suite of MGCM simulations, we have assessed plausible spatial and temporal variability in atmospheric density at high altitudes (e.g., 70-1 10 km) for seasonal dates and locations during Phase 1 aerobraking. Diagnostic tools have been developed to analyze circulation fields from the MGCM simulations, and these tools have been applied in the creation of a Mars climate catalogue database. Throughout Phase I aerobraking activities, analysis products have been provided to the MGS aerobraking atmospheric advisory group (AAG). Analyses of circulation variability at the coupling level between the MGCM and a Mars thermospheric global circulation model (MTGCM) has also been assessed. Finally, using a quasi-geostrophic dynamical formulation with the MGCM simulations, diagnosis of breaking planetary (Rossby) waves in Mars middle atmosphere has been carried out. Titles of papers presented at scientific workshops and seminars, and a publication in the scientific literature are provided.

Hollingsworth, Jeffery L.↗

The Trinity High Explosive Implosion System: The Foundation for Precision Explosive Applications

This article is set during the 1944 and 1945 final push to complete Project Y—the Manhattan Project at Los Alamos—and focuses primarily on overcoming the challenge of creating and demonstrating a successful convergent explosive implosion to turn a subcritical quantity of plutonium into a critical mass. The critical mass would then efficiently yield kilotons of trinitrotoluene (TNT)-equivalent energy in about a microsecond, demonstrating the implosion atomic bomb concept. This work culminated in the Trinity atomic test near Alamogordo on July 16, 1945. This implosion effect demarcated the approach to explosive science and technology the Laboratory has followed ever since, including development of high-explosive synthesis and formulation, small and large test and diagnostic facilities, shock dynamics theory, high-explosive system design engineering, and three-dimensional implosion modeling and simulation using some of the fastest computers in the world. This work also ushered in a period of broader application of precision high explosives in conventional munitions, demolition, mining and oil exploration, and space travel.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

X-Ray Probes of Cosmic Star-Formation History

In a previous paper we point out that the X-ray luminosity L(sub x) of a galaxy is driven by the evolution of its X-ray binary population and that the profile of L(sub x) with redshift can both serve as a diagnostic probe of the Star Formation Rate (SFR) profile and constrain evolutionary models for X-ray binaries. We update our previous work using a suite of more recently developed SFR profiles that span the currently plausible range. The first Chandra deep imaging results on L(sub x)-evolution are beginning to probe the SFR profile of bright spirals and the early results are consistent with predictions based on current SFR models. Using these new SFR profiles the resolution of the "birthrate problem" of lowmass X-ray binaries (LMXBs) and recycled, millisecond pulsars in terms of an evolving global SFR is more complete. We also discuss the possible impact of the variations in the SFR profile of individual galaxies.

Ghosh, Pranab↗

Ares I-X Ground Diagnostic Prototype

The automation of pre-launch diagnostics for launch vehicles offers three potential benefits: improving safety, reducing cost, and reducing launch delays. The Ares I-X Ground Diagnostic Prototype demonstrated anomaly detection, fault detection, fault isolation, and diagnostics for the Ares I-X first-stage Thrust Vector Control and for the associated ground hydraulics while the vehicle was in the Vehicle Assembly Building at Kennedy Space Center (KSC) and while it was on the launch pad. The prototype combines three existing tools. The first tool, TEAMS (Testability Engineering and Maintenance System), is a model-based tool from Qualtech Systems Inc. for fault isolation and diagnostics. The second tool, SHINE (Spacecraft Health Inference Engine), is a rule-based expert system that was developed at the NASA Jet Propulsion Laboratory. We developed SHINE rules for fault detection and mode identification, and used the outputs of SHINE as inputs to TEAMS. The third tool, IMS (Inductive Monitoring System), is an anomaly detection tool that was developed at NASA Ames Research Center. The three tools were integrated and deployed to KSC, where they were interfaced with live data. This paper describes how the prototype performed during the period of time before the launch, including accuracy and computer resource usage. The paper concludes with some of the lessons that we learned from the experience of developing and deploying the prototype.

Schwabacher, Mark A.↗

Structural Health Management of Damaged Aircraft Structures Using the Digital Twin Concept

The development of multidisciplinary integrated Structural Health Management (SHM) tools will enable accurate detection, and prognosis of damaged aircraft under normal and adverse conditions during flight. As part of the digital twin concept, methodologies are developed by using integrated multiphysics models, sensor information and input data from an in-service vehicle to mirror and predict the life of its corresponding physical twin. SHM tools are necessary for both damage diagnostics and prognostics for continued safe operation of damaged aircraft structures. The adverse conditions include loss of control caused by environmental factors, actuator and sensor faults or failures, and structural damage conditions. A major concern in these structures is the growth of undetected damage/cracks due to fatigue and low velocity foreign object impact that can reach a critical size during flight, resulting in loss of control of the aircraft. To avoid unstable, catastrophic propagation of damage during a flight, load levels must be maintained that are below a reduced load-carrying capacity for continued safe operation of an aircraft. Hence, a capability is needed for accurate real-time predictions of damage size and safe load carrying capacity for structures with complex damage configurations. In the present work, a procedure is developed that uses guided wave responses to interrogate damage. As the guided wave interacts with damage, the signal attenuates in some directions and reflects in others. This results in a difference in signal magnitude as well as phase shifts between signal responses for damaged and undamaged structures. Accurate estimation of damage size, location, and orientation is made by evaluating the cumulative signal responses at various pre-selected sensor locations using a genetic algorithm (GA) based optimization procedure. The damage size, location, and orientation is obtained by minimizing the difference between the reference responses and the responses obtained by wave propagation finite element analysis of different representative cracks, geometries, and sizes.

Seshadri, Banavara R.↗

Modeling Air Handling Units to Create a Diverse Fault Dataset for FDD Innovation: Lessons Learned and Recommendations

As energy management and information systems (e.g., automated fault detection and diagnostics [AFDD] tools) become more prevalent in the commercial building stock, it is important to determine the effectiveness of these technologies by benchmarking their performance. The authors have been working to develop the largest publicly available dataset of HVAC fault datasets for performance benchmarking applications, covering the most common HVAC systems and designs including chiller plants, rooftop packaged units, dual duct air handling unit and single duct air handling units. This study covers the development, modeling, and validation of a synthetic fault dataset for the air handling unit (AHU), one of the most common HVAC configurations found in the commercial building stock. Despite this being a common system, real-world time series data are scarce and usually do not span a wide range of weather conditions. Due to this limitation, two detailed AHU models, which included the single duct AHU and dual duct AHU developed in the Modelica language and HVACSIM+ were employed to carry out annual simulations of numerous common sensor faults, mechanical faults, and control sequence faults. The fault inclusive data were then validated by comparing fault effects on system performance to expected symptoms. We summarize the nature of each fault and their impacts under different weather and operation conditions. We report some lessons learnt during the efforts of validating the high volumes of the FDD data sets. Finally, we highlight considerations for FDD developers that may want to use this dataset to assess their algorithms’ performance and their improvement over time.

Casillas, Armando↗

Applying Model-Based Reasoning to the FDIR of the Command and Data Handling Subsystem of the International Space Station

All of the International Space Station (ISS) systems which require computer control depend upon the hardware and software of the Command and Data Handling System (C&DH) system, currently a network of over 30 386-class computers called Multiplexor/Dimultiplexors (MDMs)[18]. The Caution and Warning System (C&W)[7], a set of software tasks that runs on the MDMs, is responsible for detecting, classifying, and reporting errors in all ISS subsystems including the C&DH. Fault Detection, Isolation and Recovery (FDIR) of these errors is typically handled with a combination of automatic and human effort. We are developing an Advanced Diagnostic System (ADS) to augment the C&W system with decision support tools to aid in root cause analysis as well as resolve differing human and machine C&DH state estimates. These tools which draw from sources in model-based reasoning[ 16,291, will improve the speed and accuracy of flight controllers by reducing the uncertainty in C&DH state estimation, allowing for a more complete assessment of risk. We have run tests with ISS telemetry and focus on those C&W events which relate to the C&DH system itself. This paper describes our initial results and subsequent plans.

Robinson, Peter↗

Electron Cyclotron Emission–Based Separatrix Identification in ITER with OMFIT Synthetic Modeling

Accurate determination of the separatrix location is essential for understanding edge plasma behavior and optimizing confinement in tokamaks, especially in next-generation devices such as ITER. In this study, a synthetic microwave diagnostics module was developed and implemented in the OMFIT framework to assess the feasibility of an electron cyclotron emission–based separatrix detection method in ITER plasmas. Simulations were carried out using ITER H-mode equilibrium scenarios with different plasma density profiles and different pedestal widths. Here, the results show that the electron emission temperature profiles consistently exhibit an inversion pattern near the edge, with a well-defined minimum point that could serve as a proxy for the separatrix location. However, unlike in the DIII-D, the minimum point in ITER is systematically offset by approximately 2 cm into the scrape-off layer, independent of density or pedestal width, which is within the radial resolution range (2 to 5 cm) determined by the 500-MHz channel spacing. While the method does not provide the exact separatrix location, it offers a reliable indicator of the boundary region and has potential applications for real-time boundary monitoring in ITER and other future fusion devices.

Electron cyclotron emission↗

PINN surrogate of Li-ion battery models for parameter inference, Part I: Implementation and multi-fidelity hierarchies for the single-particle model

To plan and optimize energy storage demands that account for Li-ion battery aging dynamics, techniques need to be developed to diagnose battery internal states accurately and rapidly. Here, this study seeks to reduce the computational resources needed to determine a battery's internal states by replacing physics-based Li-ion battery models - such as the single-particle model (SPM) and the pseudo-2D (P2D) model - with a physics-informed neural network (PINN) surrogate. The surrogate model makes high-throughput techniques, such as Bayesian calibration, tractable to determine battery internal parameters from voltage responses. This manuscript is the first of a two-part series that introduces PINN surrogates of Li-ion battery models for parameter inference (i.e., state-of-health diagnostics). In this first part, a method is presented for constructing a PINN surrogate of the SPM. A multi-fidelity hierarchical training, where several neural nets are trained with multiple physics-loss fidelities is shown to significantly improve the surrogate accuracy when only training on the governing equation residuals. The implementation is made available in a companion repository (https://github.com/NREL/PINNSTRIPES). The techniques used to develop a PINN surrogate of the SPM are extended in Part II for the PINN surrogate for the P2D battery model, and explore the Bayesian calibration capabilities of both surrogates.

25 ENERGY STORAGE↗