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DOE OSTI2022

Flexible machine-learning interatomic potential for simulating structural disordering behavior of Li 7 La 3 Zr 2 O 12 solid electrolytes

Batteries based on solid-state electrolytes, including Li 7 La 3 Zr 2 O 12 (LLZO), promise improved safety and increased energy density; however, atomic disorder at grain boundaries and phase boundaries can severely deteriorate their performance. Machine-learning (ML) interatomic potentials offer a uniquely compelling solution for simulating chemical processes, rare events, and phase transitions associated with these complex interfaces by mixing high scalability with quantum-level accuracy, provided that they can be trained to properly address atomic disorder. To this end, we report the construction and validation of an ML potential that is specifically designed to simulate crystalline, disordered, and amorphous LLZO systems across a wide range of conditions. The ML model is based on a neural network algorithm and is trained using ab initio data. Performance tests prove that the developed ML potential can predict accurate structural and vibrational characteristics, elastic properties, and Li diffusivity of LLZO comparable to ab initio simulations. As a demonstration of its applicability to larger systems, we show that the potential can correctly capture grain boundary effects on diffusivity, as well as the thermal transition behavior of LLZO. Here these examples show that the ML potential enables simulations of transitions between well-defined and disordered structures with quantum-level accuracy at speeds thousands of times faster than ab initio methods.

25 ENERGY STORAGE↗

DOE OSTI2022

Angular dependence of the transverse Raman scattering in KDP and DKDP in geometries suitable for beam polarization control

The angular dependance of the transverse Raman scattering in potassium dihydrogen phosphate (KDP) and its deuterated analogue (DKDP) for the entire range of crystal configurations suitable for laser beam polarization control has been investigated via experimental and modeling tools. This work was made possible by simultaneously rotating a spherical sample and the pump polarization to effectively measure the angular dependance of the transverse Raman signal in 360°. This novel method, which is applicable for the investigation of the Raman scattering in optically anisotropic materials, demonstrates that the spontaneous Raman scattering signal exhibits strong angular dependence that is modulated by depolarization and polarization rotation effects generated as the Raman signal traverses the material due to its birefringence. The results show that the total signal generated by the pump beam is the sum of the signals generated by the two components that have polarization parallel and orthogonal to the optic axis. The peak signal intensity, which is of importance for high-power laser applications, depends on the orientation of the optic axis and can vary by a factor of about 2. The excellent agreement between experimental data and modeling results validates the associated models and enables one to consider optimal crystal cut designs for specific applications.

47 OTHER INSTRUMENTATION↗

NASA NTRS2016

Unsteady Aerodynamic Force Sensing from Measured Strain

A simple approach for computing unsteady aerodynamic forces from simulated measured strain data is proposed in this study. First, the deflection and slope of the structure are computed from the unsteady strain using the two-step approach. Velocities and accelerations of the structure are computed using the autoregressive moving average model, on-line parameter estimator, low-pass filter, and a least-squares curve fitting method together with analytical derivatives with respect to time. Finally, aerodynamic forces over the wing are computed using modal aerodynamic influence coefficient matrices, a rational function approximation, and a time-marching algorithm. A cantilevered rectangular wing built and tested at the NASA Langley Research Center (Hampton, Virginia, USA) in 1959 is used to validate the simple approach. Unsteady aerodynamic forces as well as wing deflections, velocities, accelerations, and strains are computed using the CFL3D computational fluid dynamics (CFD) code and an MSC/NASTRAN code (MSC Software Corporation, Newport Beach, California, USA), and these CFL3D-based results are assumed as measured quantities. Based on the measured strains, wing deflections, velocities, accelerations, and aerodynamic forces are computed using the proposed approach. These computed deflections, velocities, accelerations, and unsteady aerodynamic forces are compared with the CFL3D/NASTRAN-based results. In general, computed aerodynamic forces based on the lifting surface theory in subsonic speeds are in good agreement with the target aerodynamic forces generated using CFL3D code with the Euler equation. Excellent aeroelastic responses are obtained even with unsteady strain data under the signal to noise ratio of -9.8dB. The deflections, velocities, and accelerations at each sensor location are independent of structural and aerodynamic models. Therefore, the distributed strain data together with the current proposed approaches can be used as distributed deflection, velocity, and acceleration sensors. This research demonstrates the feasibility of obtaining induced drag and lift forces through the use of distributed sensor technology with measured strain data. An active induced drag control system thus can be designed using the two computed aerodynamic forces, induced drag and lift, to improve the fuel efficiency of an aircraft. Interpolation elements between structural finite element grids and the CFD grids and centroids are successfully incorporated with the unsteady aeroelastic computation scheme. The most critical technology for the success of the proposed approach is the robust on-line parameter estimator, since the least-squares curve fitting method depends heavily on aeroelastic system frequencies and damping factors.

shape sensing↗

DOE OSTI2022

Radon-222 Charcoal Canister Steady State Model Calibrations Performed in a Highly Controlled Environmental Chamber and a Natural Indoor Environment

Charcoal canisters are a common method of 222 Rn screening. The calibrations of different batches of activated charcoal used in different canister designs are typically performed in large volume controlled environmental chambers with known and controlled radon concentration, temperature, and humidity. Radon screening could be facilitated in locations without ready access to environmental chambers if canisters could be accurately calibrated and undergo quality control in less controlled environments. This study compares charcoal canister calibrations from a highly controlled radon chamber with calibrations from a basement storage area experiencing temporally varying radon. In addition, the impacts of exposure time and spectral region of interest selection on calibration accuracy are investigated by comparing calibrations calculated using three different choices. Approximately 30 mo after calibrations were completed, groups of canisters were exposed for different durations of time to investigate measurement accuracy and calibration validity over an extended time. A digital simulation of charcoal canister kinetics was also performed to establish limits on how stable radon must be in a space for equilibrium-based calibration to be performed there. Overall, the accuracy of measurements using calibrations from each space differed by less than 10% after 2 d exposure time, showing that carefully controlled conditions are not necessary for the accurate calibration of charcoal canisters. Furthermore, measurement accuracy differed by less than 2% for different spectral region selections. Accuracy improved slightly with canister exposure duration. Simulations suggest that radon instability is most tolerable near the beginning of canister calibration exposures, but this merits further experimental study.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2020

Bounded motion design in the Earth zonal problem using differential algebra based normal form methods

Establishing long-term relative bounded motion between orbits in perturbed dynamics is a key challenge in astrodynamics to enable cluster flight with minimum propellant expenditure. Herein, we present an approach that allows for the design of long-term relative bounded motion considering a zonal gravitational model. Entire sets of orbits are obtained via high-order Taylor expansions of Poincarè return maps about reference fixed points. The high-order normal form algorithm is used to determine a change in expansion variables of the map into normal form space, in which the phase space behavior is circular and can be easily parameterized by action–angle coordinates. The action–angle representation of the normal form coordinates is then used to parameterize the original Poincarè return map and average it over a full phase space revolution by a path integral along the angle parameterization. As a result, the averaged nodal period and drift in the ascending node are obtained, for which the bounded motion conditions are straightforwardly imposed. Sets of highly accurate bounded orbits are obtained, extending over several thousand kilometers, and valid for decades.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Process design tools and techno-economic analysis for capacitive deionization

Capacitive deionization (CDI) devices use cyclical electrosorption on porous electrode surfaces to achieve water desalination. Process modeling and design of CDI systems requires accurate treatment of the coupling among input electrical forcing, input flow rates, and system responses including salt removal dynamics, water recovery, energy storage, and dissipation. Techno-economic analyses of CDI further require a method to calculate and compare between a produced commodity (e.g. desalted water) versus capital and operational costs of the system. In this work, we demonstrate a new modeling and analysis tool for CDI developed as an installable Matlab program that allows direct numerical simulation of CDI dynamics and calculation of key performance and cost parameters. The program is provided for free and is used to run open-source Simulink models. The Simulink environment sends information to the program and allows for a drag and drop design space where users can connect CDI cells to relevant periphery blocks such as grid energy, battery, solar panel, waste disposal, and maintenance/labor cost streams. The program allows for simulation of arbitrary current forcing and arbitrary flow rate forcing of one or more CDI cells. We employ validated well-mixed reactor formulations together with a non-linear circuit model formulation that can accommodate a variety of electric double layer sub-models (e.g. for charge efficiency). The program includes a graphical user interface (GUI) to specify CDI plant parameters, specify operating conditions, run individual tests or parameter batch-mode simulations, and plot relevant results. The techno-economic models convert among dimensional streams of species (e.g. feed, desalted water, and brine), energy, and cost and enable a variety of economic estimates including levelized water costs.

42 ENGINEERING↗

DOE OSTI2025

Expediting field-effect transistor chemical sensor design with neuromorphic spiking graph neural networks

Improving the sensitive and selective detection of analytes in a variety of applications requires accelerating the rational design of field-effect transistor (FET) chemical sensors. Achieving high-performance detection relies on identifying optimal probe materials that can effectively interact with target analytes, a process traditionally driven by chemical intuition and time-consuming trial-and-error methods. To address the difficulties in probe screening for FET sensor development, this work presents a methodology that combines neuromorphic machine learning (ML) architectures, specifically a hybrid spiking graph neural network (SGNN), with an enriched dataset of physicochemical properties through semi-automated data extraction using large language models. Achieving a classification accuracy of 0.89 in predicting sensor sensitivity categories, the SGNN model outperformed traditional ML techniques by leveraging its ability to capture both global physicochemical properties and sparse topological features through a hybrid modeling framework. Next-generation sensor design was informed by the actionable insights into the connections between material properties and sensing performance offered by the SGNN framework. Through virtual screening for the detection of per- and polyfluoroalkyl substances (PFAS) as a use case, the effectiveness of the SGNN model was further validated. Density functional theory simulations confirmed graphene as a promising active material for PFAS detection as suggested by the SGNN framework. By bridging gaps in predictive modeling and data availability, this integrated approach provides a strong foundation for accelerating advancements in FET sensor design and innovation.

Ferreira, Rodrigo Pires [Univ. of Chicago, IL (Uni↗

DOE OSTI2026

Interpretable Deep Learning for Advancing Field-Enhanced Catalysis

This DOE Early Career project developed a physics-informed, interpretable AI-and-modeling framework to understand and exploit electric-field effects in heterogeneous catalysis, with ammonia cracking and synthesis as a representative pathway. The team built and validated methods to map local electric fields on metal surfaces and nanoparticles, showing that low-coordination features (tips/edges/corners) can concentrate fields by several-fold relative to flat facets. Using DFT-generated datasets, the project created physics-guided machine learning models that rapidly predict local electric fields and field-dependent adsorption energetics with near-DFT accuracy while reducing computational cost by orders of magnitude. These predictions were integrated with microkinetic modeling to quantify how field-dipole interactions reshape reaction energetics and mechanisms, enabling large increases in predicted catalytic rates and substantial reductions in operating temperature under favorable field conditions. To accelerate discovery of earth-abundant catalysts, the project combined interpretable ML screening (with electronic-structure descriptors identified as key drivers) with a generative inverse-design workflow based on diffusion models and physics constraints. The resulting closed-loop approach, linking simulation, mechanistic modeling, and AI, provides reusable tools and datasets for designing catalysts and operating conditions in field-enhanced catalysis, with broad relevance to electrostatic catalysis, plasma catalysis, electrocatalysis, and other energy-related chemical transformations.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2024

Autocalibration of the E3SM Version 2 Atmosphere Model Using a PCA-Based Surrogate for Spatial Fields

Global Climate Model tuning (calibration) is a tedious and time-consuming process, with high-dimensional input and output fields. Experts typically tune by iteratively running climate simulations with hand-picked values of tuning parameters. Many, in both the statistical and climate literature, have proposed alternative calibration methods, but most are impractical or difficult to implement. We present a practical, robust, and rigorous calibration approach on the atmosphere-only model of the Department of Energy's Energy Exascale Earth System Model (E3SM) version 2. Our approach can be summarized into two main parts: (a) the training of a surrogate that predicts E3SM output in a fraction of the time compared to running E3SM, and (b) gradient-based parameter optimization. To train the surrogate, we generate a set of designed ensemble runs that span our input parameter space and use polynomial chaos expansions on a reduced output space to fit the E3SM output. We use this surrogate in an optimization scheme to identify values of the input parameters for which our model best matches gridded spatial fields of climate observations. To validate our choice of parameters, we run E3SMv2 with the optimal parameter values and compare prediction results to expertly-tuned simulations across 45 different output fields. This flexible, robust, and automated approach is straightforward to implement, and we demonstrate that the resulting model output matches present day climate observations as well or better than the corresponding output from expert tuned parameter values, while considering high-dimensional output and operating in a fraction of the time.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2003

Three-Dimensional Magnetic Analysis Technique Developed for Evaluating Stirling Convertor Linear Alternators

The Department of Energy, the Stirling Technology Company (STC), and the NASA Glenn Research Center are developing Stirling convertors for Stirling radioisotope generators to provide electrical power for future NASA deep space missions. STC is developing the 55-We technology demonstration convertor (TDC) under contract to the Department of Energy. The Department of Energy recently named Lockheed Martin as the system integration contractor for the Stirling radioisotope generator development project. Lockheed Martin will develop the Stirling radioisotope generator engineering unit and has contract options to develop the qualification unit and the first flight unit. Glenn s role includes an in-house project to provide convertor, component, and materials testing and evaluation in support of the overall power system development. As a part of this work, Glenn has established an in-house Stirling research laboratory for testing, analyzing, and evaluating Stirling machines. STC has built four 55-We convertors for NASA, and these are being tested at Glenn. A cross-sectional view of the 55-We TDC is shown in the figure. Of critical importance to the successful development of the Stirling convertor for space power applications is the development of a lightweight and highly efficient linear alternator. In support, Glenn has been developing finite element analysis and finite element method tools for performing various linear alternator thermal and electromagnetic analyses and evaluating design configurations. A three-dimensional magnetostatic finite element model of STC's 55-We TDC linear alternator was developed to evaluate the demagnetization fields affecting the alternator magnets. Since the actual linear alternator hardware is symmetric to the quarter section about the axis of motion, only a quarter section of the alternator was modeled. The components modeled included the mover laminations, the neodymium-iron-boron magnets, the stator laminations, and the copper coils. The three-dimensional magnetostatic model was then coupled with a circuit simulator model of the alternator load and convertor controller. The coupled model was then used to generate alternator terminal voltage and current predictions. The predicted voltage and current waveforms agreed well with the experimental data, which tended to validate the accuracy of the coupled model. The model was then used to generate predictions of the demagnetization fields acting on the alternator magnets for the alternator under load. The preliminary model predictions indicate that the highest potential for demagnetization is along the inside surface of the uncovered magnets. The demagnetization field for the uncovered magnets when the mover is positioned at the end of a stroke is higher than it is when the mover is at the position of maximum induced voltage or maximum alternator current. Assuming normal load conditions, the model predicted that the onset of demagnetization is most likely to occur for magnet temperatures above 101 C.

Geng, Steven M.↗

DOE OSTI2022

Centrifuge modeling and numerical analysis on lateral performance of mono-bucket foundation for offshore wind turbines

The lateral loading performance of the mono-bucket foundation for offshore wind turbines is investigated in this study through a series of centrifuge tests and numerical analysis. Six mono-bucket models are considered to assess the influences of aspect ratio under the ultimate condition. The FE model is validated against the centrifuge test results, and the failure mechanism of the foundation is revealed. The parametric study and sensitivity analysis of the soil parameters are performed in the numerical simulations. A modified theoretical calculation method is proposed to estimate the ultimate lateral capacity of the suction bucket foundation by solving the limit equilibrium equations. A correction term is added in the calculation using the “m” method. The position of the rotation center is calculated, demonstrating a better accuracy compared to the previously reported geometric method. The modified calculation method is verified against the field test, the centrifuge test, and the laboratory test. The method is proved to be applicable in estimating the lateral performance of the mono-bucket foundation in a general form. Finally, this study aims to provide well-documented data and design references for practical engineers.

17 WIND ENERGY↗

DOE OSTI2025

Model Residuals as Shields: A Two-Level Formulation to Defend Smart Grids From Poisoning Attacks

The advancement of smart grids presents both vast opportunities and heightened cybersecurity risks. Data-driven defense mechanisms, though designed as a shield against these threats, can fall prey to poisoning attacks. We delve into regression settings, underscoring the imperative to fortify defenses against a spectrum of poison ratios, notably those above 0.5—an issue scarcely addressed in prior studies. Recognizing the susceptibilities of smart grids and their manipulable sensors, we exploit the very intent of poisoning attacks, compromising model accuracy, as our defense mechanism. Our proposed two-level optimization framework discerns between poisoned and authentic data based on model residuals, outperforming or matching existing methods in 72% to 77% of precision and 75% to 80% of recalls across various poisoning attacks, poison ratios, and datasets. Once the authentic data are identified, the trained model is adaptable for a variety of applications. Comprehensive evaluations on different smart grid datasets, pitted against myriad poisoning schemes, validate our methodology’s edge over existing methods. Here, we also shed light on the implications of model misspecification originating from temporal auto-correlation, a common feature in Internet of Things and smart grid data.

Adversarial machine learning (ML)↗

DOE OSTI2022

Overview of the MOSAiC expedition: Snow and sea ice

Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the 5 MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem, and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability across scales can be considered. On-ice observations of in situ and remote sensing properties of the different surface types over all seasons will help to improve numerical process and climate models and to establish and validate novel satellite remote sensing methods; the linkages to accompanying airborne measurements, satellite observations, and results of numerical models are discussed. We found large spatial variabilities of snow metamorphism and thermal regimes impacting sea ice growth. We conclude that the highly variable snow cover needs to be considered in more detail (in observations, remote sensing, and models) to better understand snow-related feedback processes. The ice pack revealed rapid transformations and motions along the drift in all seasons. The number of coupled ice–ocean interface processes observed in detail are expected to guide upcoming research with respect to the changing Arctic sea ice.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Integrated FHR technology development: Tritium management, materials testing, salt chemistry control, thermal hydraulics and neutronics, associated benchmarking and commercial basis

This report summarizes the results of a 3-year Integrated Research Project (IRP) sponsored by the U.S. Department of Energy to address major technical challenges in the development of the Fluoride-salt-cooled High-temperature Reactor (FHR). The IRP universities included the Massachusetts Institute of Technology (MIT), the University of California at Berkeley (UCB), the University of Wisconsin (UW), and the University of New Mexico (UNM). The FHR is a new reactor concept less than 20 years old that combines (1) a clean fluoride salt coolant, (2) the graphite-matrix coated-particle fuel originally developed for High- Temperature Gas-Cooled Reactors and (3) passive decay heat removal systems from sodium fast reactors. The base-line design is a pebble-bed FHR that delivers heat between 600 to 700°C with a 7 Li 2 BeF 4 (flibe) salt coolant to the power cycle or industrial users. The Executive Summary describes what was accomplished and summarizes major conclusions. The main report contains stand-alone sections in each major area of work. Highlights are summarized below. Tritium. The coolant salt produces tritium necessitating understanding and control of tritium. Experimental work included measuring hydrogen uptake on carbon, tritium uptake during irradiation of graphite in 700°C salt and the permeability of tritium through metals with and without coatings. An FHR systems model was developed to predict tritium behavior and enable design of tritium control systems. The leading candidate for tritium removal from the flibe salt is carbon bed outside the reactor core. Thermal hydraulics and Neutronics. A 10-meter high FHR integral effects test facility, using Dowtherm A®, has been built and used to simulate the integral response of a representative FHR to improve understanding of FHR thermal hydraulics and validate thermal hydraulics codes used for the FHR. Neutronic analysis included code-to-code benchmarking, multiphysics modeling, uncertainty analysis for nuclear data uncertainties and shielding analysis. Twisted-tube heat exchangers were examined that may provide significant cost reductions because of their improved heat-transfer performance with liquid salts. The impacts on safety and design caused by uncertainties in physical properties of the salt were assessed with recommendations on where added physical property measurements are needed. Work began on understanding radiative heat transfer that becomes important in salt systems at higher temperatures. Materials. Static corrosion tests were conducted on graphite and materials in 700°C salt -- both in the UW laboratory and in the MIT reactor. In addition to static corrosion testing, a circulating salt corrosion loop was built and is operating. Methods to measure salt properties including redox were developed. The presence of carbon increases corrosion. With good redox control, the evidence indicates stainless steel can be used as a material of construction. Benchmarking. An additional series of workshops where held to enable benchmarking and comparison of results between different investigators. Commercialization. The FHR delivers higher average-temperature (~650°C) heat to the power cycle or industry than other reactors. This enables power cycles with lower-cost heat storage for variable electricity to the grid while the reactor operates at base-load -- providing a major competitive advantage by maximizing revenue from electricity sales. In October, 2016, a new startup company named Kairos Power was formed, and opened its first office in Jack London Square, Oakland, California, in January 2017. Kairos Power exists largely due to the work that was accomplished by this IRP and the previous DOE-funded FHR IRP that performed research on FHR technology from 2012 to 2015. In September, 2018, as this IRP is concluding, Kairos Power was staffed at 60 full time employees, working to develop technology derived from this IRP. Many of these employees worked with the IRP before joining Kairos Power 1 (https://kairospower.com). Other students and researchers from this IRP have joined other startup companies, including the Terrapower Molten Chloride Fast Reactor and the Terrestrial Energy development efforts.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS2007

Development of a Tunable Electromechanical Acoustic Liner for Engine Nacelles

This report describes the development of a tunable electromechanical Helmholtz resonator (EMHR) for engine nacelles using smart materials technology. This effort addresses both near-term and long-term goals for tunable electromechanical acoustic liner technology for the Quiet Aircraft Technology (QAT) Program. Analytical models, i.e. lumped element model (LEM) and transfer matrix (TM) representation of the EMHR, have been developed to predict the acoustic behavior of the EMHR. The models have been implemented in a MATLAB program and used to compare with measurement results. Moreover, the prediction performance of models is further improved with the aid of parameter extraction of the piezoelectric backplate. The EMHR has been experimentally investigated using standard two-microphone method (TMM). The measurement results validated both the LEM and TM models of the EMHR. Good agreement between predicted and measured impedance is obtained. Short- and open circuit loads define the limits of the tuning range using resistive and capacitive loads. There is approximately a 9% tuning limit under these conditions for the non-optimized resonator configuration studied. Inductive shunt loads result in a 3 degree-of-freedom DOF) system and an enhanced tuning range of over 20% that is not restricted by the short- and open-circuit limits. Damping coefficient ' measurements for piezoelectric backplates in a vacuum chamber are also performed and indicate that the damping is dominated by the structural damping losses, such as compliant boundaries, and other intrinsic loss mechanisms. Based on models of the EMHR, a Pareto optimization design of the EMHR has been performed for the EMHR with non-inductive loads. The EMHR with non-inductive loads is a 2DOF system with two resonant fiequencies. The tuning ranges of the two resonant frequencies of the EMHR with non-inductive loads cannot be optimized simultaneously; a trade-off (i.e., a Pareto solution) must be reached. The Pareto solution provides the information for a designer that shows how design trade-offs can be used to satisfy specific design requirements. The optimization design of the EMHR with inductive loads aims at optimal tuning of these three resonant fiequencies. The results indicate that it is possible to keep the acoustic reactance of the resonator close to a constant over a given frequency range. An effort to mimic the second layer of the NASA 2DOF liner using a piezoelectric composite diaphragm has been made. The optimal acoustic reactance of the second layer of the NASA 2DOF liner is achieved using a thin PVDF composite diaphragm, but matching the acoustic resistance requires further investigation. Acoustic energy harvesting is achieved by connecting the EMHR to an energy reclamation circuit that converts the ac voltage signal across the piezoceramic to a conditioned dc signal. Energy harvesting experiment yields 16 m W continuous power for an incident SPL of 153 dB. Such a level is sufficient to power a variety of low power electronic devices. Finally, technology transfer has been achieved by converting the original NASA ZKTL FORTRAN code to a MATLAB code while incorporating the models of the EMHR. Initial studies indicate that the EMHR is a promising technology that may enable lowpower, light weight, tunable engine nacelle liners. This technology, however, is very immature, and additional developments are required. Recommendations for future work include testing of sample EMHR liner designs in NASA Langley s normal incidence dual-waveguide and the grazing-incidence flow facility to evaluating both the impedance characteristics as well as the energy reclamation abilities. Additional design work is required for more complex tuning circuits with greater performance. Poor electromechanical coupling limited the electromechanical tuning capabilities of the proof of concept EMHR. Different materials than those studies and perhaps novel composite material systems may dramatically improvehe electromechanical coupling. Such improvements are essential to improved mimicking of existing double layer liners.

Liu, Fei↗

NASA NTRSDate not supplied

Combining Disparate Measures of Metabolic Rate During Simulated Spacewalks

Scientists from NASA's Extravehicular Activities (EVA) Physiology Systems and Performance Project help design space suits for future missions, during which astronauts are expected to perform EVA activities on the Lunar or Martian surface. During an EVA, an astronaut's integrated metabolic rate is used to predict how much longer the activity can continue and still provide a safe margin of remaining consumables. For EVAs in the Apollo era, NASA physicians monitored live data feeds of heart rate, O 2 consumption, and liquid cooled garment (LCG) temperatures, which were subjectively combined or compared to produce an estimate of metabolic rate. But these multiple data feeds sometimes provided conflicting estimates of metabolic rate, making real-time calculations of remaining time difficult for physician/monitors. Currently, designs planned for the Constellation Program EVAs utilize an automated, but largely heuristic methodology for incorporating the above three measurements, plus an additional one - CO 2 production, ignoring data that appears in conflict; however a more rigorous model-based approach is desirable. In this study, we show how principal axis factor analysis, in combination with OLS regression and LOWESS smoothing can be used to estimate metabolic rate as a data-driven weighted average of heart rate, O 2 consumption, LCG temperature data, and CO 2 production. Preliminary results suggest less sensitivity to occasional spikes in observed data feeds, and reasonable within-subject reproducibility when applied to subsequent tasks. These methods do not require physician monitoring and as such can be automated in the electronic components of future space suits. With additional validation, our models show promise for increasing astronaut safety, while reducing the need for and potential errors associated with human monitoring of multiple systems.

Alan H Feiveson↗

NASA NTRS2014

Computational Prediction of Pressure and Thermal Environments in the Flame Trench With Launch Vehicles

One of the key objectives for the development of the 21st Century Space Launch Com- plex is to provide the exibility needed to support evolving launch vehicles and spacecrafts with enhanced range capacity. The launch complex needs to support various proprietary and commercial vehicles with widely di erent needs. The design of a multi-purpose main ame de ector supporting many di erent launch vehicles becomes a very challenging task when considering that even small geometric changes may have a strong impact on the pressure and thermal environment. The physical and geometric complexity encountered at the launch site require the use of state-of-the-art Computational Fluid Dynamics (CFD) tools to predict the pressure and thermal environments. Due to harsh conditions encountered in the launch environment, currently available CFD methods which are frequently employed for aerodynamic and ther- mal load predictions in aerospace applications, reach their limits of validity. This paper provides an in-depth discussion on the computational and physical challenges encountered when attempting to provide a detailed description of the ow eld in the launch environ- ment. Several modeling aspects, such as viscous versus inviscid calculations, single-species versus multiple-species ow models, and calorically perfect gas versus thermally perfect gas, are discussed. The Space Shuttle and the Falcon Heavy launch vehicles are used to study di erent engine and geometric con gurations. Finally, we provide a discussion on traditional analytical tools which have been used to provide estimates on the expected pressure and thermal loads.

thermal↗

DOE OSTI2023

High-fidelity Experiments of Turbulent Buoyant Jets from Simultaneous Particle Image Velocimetry and Laser Induced Fluorescence

Accurate models of turbulent buoyant flows are essential for the design of nuclear reactors thermal hydraulics and passive safety systems. However, available models fail to fully capture the physics of turbulent mixing when buoyancy becomes predominant with respect to momentum. Therefore, high-fidelity experiments of well-controlled fundamental flows are needed to develop and validate more accurate models. We performed experiments of positive and negative turbulent buoyant jets, both in uniform and stratified environments, with the aim of understanding the thermal hydraulics of turbulent mixing with variable density and providing high-fidelity data for the development and validation of turbulence models. Non-intrusive, simultaneous Particle Image Velocimetry and Laser Induced Fluorescence measurements were carried out to acquire instantaneous velocity and concentration fields on a vertical section parallel to the axis of a jet in the self-similar region. The Refractive Index Matching method was applied to measure high-resolution buoyant jets with up to 8.6% density difference. These data are free of the typical errors that characterize optical measurements of buoyancy driven flows (e.g., natural and mixed convection) where the refractive index of the fluid is inhomogeneous throughout the measurement domain. Turbulent statistics and entrainment of buoyant jets in uniform and stratified environments are presented. These data are compared with non-buoyant jets in uniform environment, as a reference to investigate the effects of buoyancy and stratification on turbulent mixing. The results will be used for the assessment of current turbulence models and as basis for the development of a new one that captures turbulent mixing.

42 ENGINEERING↗