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At least 127 records · Page 7

Upper troposphere dust belt formation processes vary seasonally and spatially in the Northern Hemisphere

Dust aerosols impact global energy balance substantially by acting as efficient ice nuclei to alter cold cloud properties. However, the estimate of dust indirect effect remains uncertain due to simulating dust distributions poorly and lacking reliable dust observations, especially in the upper-troposphere. Here, we characterize and understand upper-troposphere dust sources and transport with an improved dust dataset derived from A-train satellite lidar and radar measurements and an air parcel trajectory model. The distinct upper-troposphere dust belt over the northern hemisphere has seasonally varying base and top heights of 3.65 ± 2.84 and 8.35 ± 1.50 km above mean sea level and its column loading is strongest during spring (March-April-May). The out-of-phase annual cycles of mid-level dust concentration and westerly wind over source regions control the seasonal upper-tropospheric dust loading variations. African deserts contribute the most (46.3%) to the upper-troposphere dust belt in spring and the synoptic trough is the leading (49%) dust lifting mechanism.

54 ENVIRONMENTAL SCIENCES↗

Stellar models with microscopic diffusion and rotational mixing. 1: Application to the Sun

The Yale stellar evolution code has been modified to include the combined effects of diffusion and rotational mixing on H-1, H-4, and the trace elements He, Li-6, Li-7, and Be-9. The interaction between rotational mixing and diffusion is studied by calculating a number of calibrated solar models. The rotational mixing inhibits the diffusion in the outer parts of the models, leading to a decrease in the envelope diffusion by 25%-50%. Conversely, diffusion leads to gradients in mean molecular weight which can inhibit the rotational mixing. The degree to which gradients in mean molecular weight inhibit the rotational mixing is somewhat uncertain. A comparison with the observed solar oblateness suggests that gradients in the mean molecular weight play a smaller role in inhibiting the rotational mixing than previously believed. This is reinforced by the fact that the model with the standard value for the inhibiting effect of mean molecular weight on the rotational mixing depletes no Li on the main sequence. This is clear in contrast to the observations. A reduction in the inhibiting effect of mean molecular weight gradients by a factor of 10 loads to noticeable main-sequence Li depletion.

Chaboyer, Brian↗

Power System Resilience Enhancement in Typhoons Using a Three-Stage Day-Ahead Unit Commitment

In this work, we propose a three-stage resilient unit commitment model which considers uncertain typhoon paths and line outages to improve the power system resilience against typhoon events. The proposed solution coordinates resources in response to the worst-case scenario for each possible typhoon path. The optimal decision is based on the characterization of the power system schedule into three stages of preventive control, emergency control, and restoration. Preventive control is performed before the typhoon occurs by quickly adjusting the three-stage resilient unit commitment schedule; emergency control is conducted during the typhoon by shedding local loads to meet the power balance, while other control strategies are assumed to be unavailable due to possible interruptions in the communication system; restoration is realized after the typhoon, when resources are optimally dispatched to repair the outages of critical devices and recover the normal operation state of the power system quickly. Considering the typhoon path uncertainty, we have introduced a stochastic model for possible typhoon paths where all possible affected lines along each typhoon path are assumed to be on outage during the typhoon. Accordingly, we explore the strategy for co-optimizing the three stages in unit commitment. The proposed model is tested on the IEEE 118-bus system and the real-world provincial system to verify its effectiveness.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Reducing heat load density with asymmetric and inclined double-crystal monochromators: principles and requirements revisited

Asymmetric double-crystal monochromators (aDCMs) and inclined DCMs (iDCMs) can significantly expand the X-ray beam footprint and consequently reduce the heat load density and gradient. Based on rigorous dynamical theory calculations, the major principles and properties of aDCMs and iDCMs are presented to guide their design and development, particularly for fourth-generation synchrotrons. In addition to the large beam footprint, aDCMs have very large bandwidths (up to ∼10 eV) and angular acceptance, but the narrow angular acceptance of the second crystal requires precise control of the relative orientations and strains. Based on Fourier coupled-wave diffraction theory calculations, it is rigorously proved that the iDCM has almost the same properties as the conventional symmetric DCM, including the efficiency, angular acceptance, bandwidth, tuning energy range and sensitivity to misalignment. The exception is that, for the extremely inclined geometry that can achieve very large footprint expansion, the iDCM has (beneficially) a larger bandwidth and wider angular acceptance. Inclined diffraction has the `rho-kick effect' that can be cancelled by the second reflection of the iDCM (even with misalignment), except that inhomogeneous strains may cause non-uniform rho-kick angles. At present, fabrication/mounting-induced strains pose low risk since they can be controlled to <0.5 µrad over large areas. The only uncertain challenge is the thermally induced strains, yet it is estimated that these strains are naturally lowered by the large footprint and may be further mitigated by optimized cryogenic cooling to the 1–2 µrad level. Overall, aDCMs and iDCMs have more stringent requirements than normal DCMs, but they are feasible schemes in practice.

asymmetric monochromator↗

A Machine Learning-based Reliability Evaluation Model for Integrated Power-Gas Systems

This article proposes a hybrid machine learning method for the reliability evaluation of integrated power-gas systems (IPGS) under the uncertain component failure probability distributions. The Random Forest (RF) method is designed to select important features to solve the insufficient quantity of data and the curse of dimensionality problems. The Extreme Gradient Boosting (XGBoost) regression algorithm is developed to quantify the relationship between the uncertain parameters and reliability metrics. Moreover, a ten-fold cross-validation method is employed to further improve the accuracy of the regression model. Simulation results on three test systems show that the proposed method can achieve high accuracy for the reliability evaluation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

An Iterative Response-Surface-Based Approach for Chance-Constrained AC Optimal Power Flow Considering Dependent Uncertainty

A modern power system is characterized by a stochastic variation of the loads and an increasing penetration of renewable energy generation, which results in large uncertainties in its states. These uncertainties bring formidable challenges to the power system planning and operation process. To address these challenges, we propose a cost-effective, iterative response-surface-based approach for the chance-constrained AC optimal power-flow problem that aims to ensure the secure operation of the power systems considering dependent uncertainties. Starting from a stochastic-sampling-based framework, we first utilize the copula theory to simulate the dependence among multivariate uncertain inputs. Then, to reduce the prohibitive computational time required in the traditional Monte-Carlo method, we propose, instead of using the original complicated power-system model, to rely on a polynomial-chaos-based response surface. This response surface allows us to efficiently evaluate the time-consuming power-system model at arbitrary distributed sampled values with a negligible computational cost. This further enables us to efficiently conduct an online stochastic testing for the system states that not only screens out the statistical active constraints, but also assists in a better design of the tightened bounds without using any Gaussian or symmetric assumption. Finally, an iterative procedure is executed to fine-tune the optimal solution that better satisfies a predefined probability. The simulations conducted in multiple test systems demonstrate the excellent performance of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Continuing Studies of Planetary Atmospheres Associated with Experiments on the Galileo Jupiter Probe and Infrared Observations of Venus

The results of the nephelometer experiment conducted aboard the Probe of the Galileo mission to Jupiter are presented. The tenuous clouds and sparse particulate matter in the relatively particle-free 5-micron "hot spot" region of the Probe's descent were documented from about 0.46 bars to about 12 bars. Three regions of apparent coherent structure were noted, in addition to many indications of extremely small particle concentrations along the descent path. From the first valid measurement at about 0.46 bars down to about 0.55 bars a feeble decaying lower portion of a cloud, corresponding with the predicted ammonia particle cloud, was encountered. A denser, but still very modest, particle structure was present in the pressure regime extending from about 0.76 to a distinctive base at 1.34 bars, and is compatible with the expected ammonium hydrosulfide cloud. No massive water cloud was encountered, although below the second structure, a small, vertically thin layer at about 1.65 bars may be detached from the cloud above, but may also be water condensation, compatible with reported measurements of water abundance from other Galileo Mission experiments. A third small signal region, extending from about 1.9 to 4.5 bars, exhibited quite weak but still distinctive structure, and, although the identification of the light scatterers in this region is uncertain, may also be a water cloud perhaps associated with lateral atmospheric motion and/or reduced to a small mass density by atmospheric subsidence or other explanations. Rough descriptions of the particle size distributions and cloud properties in these regions have been derived, although they may be imprecise because of the small signals and experimental difficulties. These descriptions document the small number densities of particles, the moderate particle sizes, generally in the slightly submicron to few micron range, and the resulting small optical depths, mass densities due to particles, column particle number loading and column mass loading in the atmosphere encountered by the Galileo Probe during its descent.

Ragent, Boris↗

Continuing Studies of Planetary Atmospheres Associated With Experiments on the Galileo Jupiter Probe and Infrared Observations of Venus

The results of the nephelometer experiment conducted aboard the Probe of the Galileo mission to Jupiter are presented. The tenuous clouds and sparse particulate matter in the relatively particle-free 5-micron "hot spot" region of the Probe's descent were documented from about 0.46 bars to about 12 bars. Three regions of apparent coherent structure were noted, in addition to many indications of extremely small particle concentrations along the descent path. From the first valid measurement at about 0.46 bars down to about 0.55 bars a feeble decaying lower portion of a cloud, corresponding with the predicted ammonia particle cloud, was encountered. A denser, but still very modest, particle structure was present in the pressure regime extending from about 0.76 to a distinctive base at 1.34 bars, and is compatible with the expected ammonium hydrosulfide cloud. No massive water cloud was encountered, although below the second structure, a small, vertically thin layer at about 1.65 bars may be detached from the cloud above, but may also be water condensation, compatible with reported measurements of water abundance from other Galileo Mission experiments. A third small signal region, extending from about 1.9 to 4.5 bars, exhibited quite weak but still distinctive structure, and, although the identification of the light scatterers in this region is uncertain, may also be a water cloud perhaps associated with lateral atmospheric motion and/or reduced to a small mass density by atmospheric subsidence or other explanations. Rough descriptions of the particle size distributions and cloud properties in these regions have been derived, although they may be imprecise because of the small signals and experimental difficulties. These descriptions document the small number densities of particles, the moderate particle sizes, generally in the slightly submicron to few micron range, and the resulting small optical depths, mass densities due to particles, column particle number loading and column mass loading in the atmosphere encountered by the Galileo Probe during its descent.

Goodman,Jindra↗

Physics and technology considerations for the deuterium–tritium fuel cycle and conditions for tritium fuel self sufficiency

The tritium aspects of the DT fuel cycle embody some of the most challenging feasibility and attractiveness issues in the development of fusion systems. The review and analyses in this paper provide important information to understand and quantify these challenges and to define the phase space of plasma physics and fusion technology parameters and features that must guide a serious R&D in the world fusion program. We focus in particular on components, issues and R&D necessary to satisfy three 'principal requirements': (1) achieving tritium self-sufficiency within the fusion system, (2) providing a tritium inventory for the initial start-up of a fusion facility, and (3) managing the safety and biological hazards of tritium. A primary conclusion is that the physics and technology state-of-the-art will not enable DEMO and future power plants to satisfy these principal requirements. We quantify goals and define specific areas and ideas for physics and technology R&D to meet these requirements. A powerful fuel cycle dynamics model was developed to calculate time-dependent tritium inventories and flow rates in all parts and components of the fuel cycle for different ranges of parameters and physics and technology conditions. Dynamics modeling analyses show that the key parameters affecting tritium inventories, tritium start-up inventory, and tritium self-sufficiency are the tritium burn fraction in the plasma (f b ), fueling efficiency (η f ), processing time of plasma exhaust in the inner fuel cycle (t p ), reactor availability factor (AF), reserve time (tr) which determines the reserve tritium inventory needed in the storage system in order to keep the plant operational for time t r in case of any malfunction of any part of the tritium processing system, and the doubling time (t d ). Results show that η f f b > 2% and processing time of 1–4 h are required to achieve tritium self-sufficiency with reasonable confidence. For η f f b = 2% and processing time of 4 h, the tritium start-up inventory required for a 3 GW fusion reactor is ~11 kg, while it is <5 kg if η f f b = 5% and the processing time is 1 h. To achieve these stringent requirements, a serious R&D program in physics and technology is necessary. The EU-DEMO direct internal recycling concept that carries fuel directly from the plasma exhaust gas to the fueling systems without going through the isotope separation system reduces the overall processing time and tritium inventories and has positive effects on the required tritium breeding ratio (TBR R ). A significant finding is the strong dependence of tritium self-sufficiency on the reactor availability factor. Simulations show that tritium self-sufficiency is: impossible if AF < 10% for any η f f b , possible if AF > 30% and 1% ≤ η f f b ≤ 2%, and achievable with reasonable confidence if AF > 50% and η f f b > 2%. These results are of particular concern in light of the low availability factor predicted for the near-term plasma-based experimental facilities (e.g. FNSF, VNS, CTF), and can have repercussions on tritium economy in DEMO reactors as well, unless significant advancements in RAMI are made. There is a linear dependency between the tritium start-up inventory and the fusion power. The required tritium start-up inventory for a fusion facility of 100 MW fusion power is as small as 1 kg. Since fusion power plants will have large powers for better economics, it is important to maintain a 'reserve' tritium inventory in the tritium storage system to continue to fuel the plasma and avoid plant shutdown in case of malfunctions of some parts of the tritium processing lines. But our results show that a reserve time as short as 24 h leads to unacceptable reserve and start-up inventory requirements. Therefore, high reliability and fast maintainability of all components in the fuel cycle are necessary in order to avoid the need for storing reserve tritium inventory sufficient for continued fusion facility operation for more than a few hours. The physics aspects of plasma fueling, tritium burn fraction, and particle and power exhaust are highly interrelated and complex, and predictions for DEMO and power reactors are highly uncertain because of lack of experiments with burning plasma. Fueling by pellet injection on the high field side of tokamak has evolved to be the preferred method to fuel a burning plasma. Extrapolation from the DIII-D penetration scaling shows fueling efficiency expected in DEMO to be <25%, but such extrapolations are highly uncertain. The fueling efficiency of gas in a reactor relevant regime is expected to be extremely poor and not very useful for getting tritium into the core plasma efficiently. Gas fueling will nonetheless be useful for feedback control of the divertor operating parameters. Extensive modeling has been carried out to predict burn fraction, fueling requirements, and fueling efficiency for ITER, DEMO, and beyond. The fueling rate required to operate Q = 10 ITER plasmas in order to provide the required core fueling, helium exhaust and radiative divertor plasma conditions for acceptable divertor power loads was calculated. If this fueling is performed with a 50–50 DT mix, the tritium burn fraction in ITER would be ~0.36%, which is too low to satisfy the self-sufficiency conditions derived from the dynamics modeling for fusion reactors. Extrapolation to DEMO using this approach would also yield similarly low burn fraction. Extensive analysis presented shows that specific features of edge neutral dynamics in ITER and fusion reactors, which are different from present experiments, open possibilities for optimization of tritium fueling and thus to improve the burn fraction. Using only tritium in pellet fueling of the plasma core, and only deuterium for edge density, divertor power load and ELM control results in significant increase of the burn fraction to 1.8–3.6%. These estimates are performed with physics models whose results cannot be fully validated for ITER and DEMO plasma conditions since these cannot be achieved in present tokamak experiments. Thus, several uncertainties remain regarding particle transport and scenario requirements in ITER and DEMO. The safety standard requirements for protection of the public and release guidelines for tritium have been reviewed. General safety approaches including minimizing tritium inventories, reducing tritium permeation through materials, and decontaminating material for waste disposal have been suggested.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A review on the integration of probabilistic solar forecasting in power systems

As one of the fastest growing renewable energy sources, the integration of solar power poses great challenges to power systems due to its variable and uncertain nature. As an effective approach to promote the integration of solar power in power systems, the value of probabilistic forecasts is being increasingly recognized in the recent decade. While the current use of probabilistic forecasts in power systems is limited, enormous amount of research has been conducted to promote the adoption of probabilistic forecasts and many methods have been proposed. This paper gives a comprehensive review on how probabilistic solar forecasts are utilized in power systems to address the challenges. Potential methods to deal with uncertainties in power systems are summarized, such as probabilistic load flow models, stochastic optimization, robust optimization, and chance constraints. Additionally, specific areas where these methods can be applied are discussed and state-of-the-art studies are summarized.

14 SOLAR ENERGY↗

Optimization-based calibration of hydrodynamic drag coefficients for a semisubmersible platform using experimental data of an irregular sea state

For the simulation of the coupled dynamic response of floating offshore wind turbines, it is crucial to calibrate the hydrodynamic damping with experimental data. The aim of this work is to find a set of hydrodynamic drag coefficients for the semisubmersible platform of the Offshore Code Comparison Collaboration, Continuation, with Correlation and unCertainity (OC6) project which provides suitable results for an irregular sea state. Due to the complex interaction of several degrees of freedom (DOF), it is common to calibrate drag coefficients with the time series of decay tests. However, applying these drag coefficients for the simulation of an irregular sea state results in misprediction of the motions. By using numerical optimization, it is possible to calibrate multiple drag coefficients simultaneously and effectively, while also considering several DOF. This work considers time series of structural displacements from wave tank tests of the OC6 project and from simulations of the same load cases in OpenFAST. Results are transferred into the frequency domain and the deviation between power spectral densities of surge, pitch and heave from experiment and numerical simulation is used as an objective function to obtain the best fitting drag coefficients. This novel numerical optimization approach enables finding one set of drag coefficients for different load cases, which is a major improvement compared to decay-test-tuned drag coefficients.

42 ENGINEERING↗

High-frequency Data Integration for Landscape Model Calibration of Carbon Fluxes Across Diverse Tidal Marshes

Terrestrial Aquatic Interfaces (TAIs), and tidal wetlands in particular, store large amounts of carbon yet are not well represented in Earth System Models (ESMs). Predictions of carbon cycling and greenhouse gas (GHG) emissions in tidal wetlands are highly uncertain. Eddy covariance (EC) towers provide ecosystem-scale GHG flux data at a temporal resolution (every 30min) that is helpful for parameterizing and improving mechanistic realism in ESMs. We propose to use a network of eddy covariance towers and standardized ancillary data streams, along with mesocosm experiments and statistical analyses, across diverse tidal wetlands of North America to develop and improve biogeochemical modeling at the TAI. Our overarching objective is to improve understanding and process-based modeling of gross primary productivity (GPP) and CH4 emission responses, both non-linear and asynchronous, to stressors including plant inundation, disturbance, salinity and nitrogen loading.

54 ENVIRONMENTAL SCIENCES↗

Achieving high rate performance in hybrid pristine-recycled cathodes using model-informed electrode designs

Direct recycling lithium-ion battery cathodes, a process that retains the engineered oxide structures from end-of-life materials, presents a cost-effective and energy-efficient alternative to other battery recycling methods. However, while direct-recycled cathodes have demonstrated performance comparable to that of pristine materials at low cycling rates, their high-rate performance remains uncertain. Morphology changes in cathode particles, a main mode of degradation, directly impact rate performance by limiting surface kinetics and solid-phase diffusion. If direct recycling processes do not sufficiently restore pristine-like morphologies, the recycled materials may retain structural defects that hinder high-rate performance. The present work uses a physics-based pseudo-2D model to simulate hybrid electrodes with pristine and artificially “aged/recycled” NMC materials to investigate potential impacts of incorporating performance-limited aged cathode materials into cells. The study highlights how differences in transport and kinetic properties can influence rate capabilities in mixed electrodes — particularly in high-loading cells in high-demand applications. However, model results also reveal a possible mitigation strategy via dual-layer electrode architectures with lower-performing materials positioned near the current collector. Simulations of 4.0 mAh cm −2 cells cycled at 4C using a dual-layer architecture provided approximately 5%–30% more capacity in constant-current protocols compared to homogeneously blended electrode architectures with the same loadings and mixed-material compositions. These findings highlight the importance of strategic electrode design in minimizing potential performance losses and facilitating the integration of recycled materials into high-performance batteries, advancing sustainable and cost-effective battery manufacturing.

25 ENERGY STORAGE↗

Validation of Satellite Aerosol Retrievals from AERONET Ground-Based Measurements

Accurate and comprehensive assessment of the parameters that control key atmospheric and biospheric processes including assessment of anthropogenic effects on climate change is a fundamental measurement objective of NASA's EOS program (King and Greenstone, 1999). Satellite assessment programs and associated global climate models require validation and additional parameterization with frequent reliable ground-based observations. A critical and highly uncertain element of the measurement program is characterization of tropospheric aerosols requiring basic observations of aerosols optical and microphysical properties. Unfortunately as yet we do not know the aerosol burden man is contributing to the atmosphere and thus we will have no definitive measure of change for the future. This lack of aerosol assessment is the impetus for some of the EOS measurement activities (Kaufman et al., 1997; King et al., 1999) and the formation of the AERONET program (Holben et al., 1998). The goals of the AERONET program are to develop long term monitoring at globally distributed sites providing critical data for multiannual trend changes in aerosol loading and optical properties with the specific goal of providing a data base for validation of satellite derived aerosol optical properties. The AERONET program has evolved into an international federated network of approximately 100 ground-based remote sensing monitoring stations to characterize the optical and microphysical properties of aerosols.

Holben, Brent↗

Calibration for Thrust and Airflow Measurements in the CE-22 Advanced Nozzle Test Facility

CE-22 facility procedures and measurements for thrust and airflow calibration obtained with choked-flow ASME nozzles are presented. Six calibration nozzles are used at an inlet total pressure from 20 to 48 psia. Throat areas are from 9.9986 to 39.986 sq. in.. Throat Reynolds number varies from 1.8 to 7.9 million. Nozzle gross thrust coefficient (CFG) uncertainty is 0.25 to 0.75 percent, with smaller uncertainly generally for larger nozzles and higher inlet total pressure. Nozzle discharge coefficient (CDN) uncertainty is 0.15 percent or less for all the data. ASME nozzle calibrations need to be done before and after research model testing to achieve these uncertainties. In addition, facility capability in terms of nozzle pressure ratio (NPR) and nozzle airflow are determined. Nozzle pressure ratio of 50 or more is obtainable at 40 psia for throat areas between 20 and 30 sq. in.. Also presented are results for two of the ASME nozzles vectored at 10deg, a dead-weight check of the vertical (perpendicular to the jet axis) force measurement, a calibration of load cell forces for the effects of facility tank deflection with tank pressure, and the calibration of the metric-break labyrinth seal.

Werner, Roger A.↗

Submersed Macrophyte Density Regulates Aquatic Greenhouse Gas Emissions

Abstract Shallow freshwater ecosystems emit large amounts of greenhouse gases (GHGs), such as carbon dioxide (CO 2 ) and methane (CH 4 ), yet emissions are highly variable. The role that aquatic macrophytes play in regulating aquatic GHG emissions is uncertain despite their ability to dominate shallow waterbodies. Here, we studied the effects of submersed macrophyte (Ceratophyllum demersum) density on CO 2 and CH 4 concentrations and fluxes. We conducted a 61‐days experiment using mesocosms containing one of the followingC.demersumdensity treatments: 0, 10, 20, or 30 individual shoots (n = 3). We found that high densityC.demersumhad the highest CO 2 and CH 4 surface water concentrations and emissions while there was no significant difference in CH 4 in the low and medium densities and no plant control. The high density treatment lost biomass over the course of the experiment, indicating die‐off and additions of organic matter to the sediment. High organic matter loading and low dissolved oxygen likely stimulated GHG production in the high density treatment. Our results emphasize that submersed macrophyte density and periods of growth and dieback are important in regulating GHG emissions, which may help explain why shallow waterbodies are high yet variable sources of GHGs to the atmosphere.

Environmental Sciences & Ecology↗

Ergonomic Evaluation of Space Shuttle Light-Weight Seat Lever Position and Operation

During a Shuttle flight in the early part of 1999, one of the crewmembers was unable to operate the backrest lever for the light-weight seat in microgravity. It is essential that the crewmembers are able to adjust this back-rest lever, which is titled forward 2 degrees from vertical during launch and then moved backwards to 10 degrees aft of vertical upon reaching orbit. This adjustment is needed to cushion the crewmembers during an inadvertent crash landing situation. The original Shuttle seats, which had seat controls located on the front left and right sides of the seat, were replaced recently with the new light-weight seats. The controls for these new, seats were moved to the night side with one control at the front and the other at the back. While it was uncertain whether the problem encountered was unique to that crewmember or not it was clear to the personnel responsible for maintaining the Shuttle seats that not knowing the cause of the problem posed a safety concern for NASA. Hence the Anthropometry and Biomechanics Facility (ABF) of the Johnson Space Center was requested to perform an evaluation of the seat controls and provide NASA with appropriate recommendations on whether the seat lever positions and operations should be modified. The ABF designed an experiment to investigate the amount of pull force exerted by subjects, wearing an unpressurized or pressurized crew launch escape suit, when controls were placed in the front and back (on the right side) of the light-weight seat. Single-axis load cells were attached to the seat levers, which measured the maximum static pull forces that were exerted by the subjects. Twelve subjects, six male and six female, participated in this study. Each subject was asked to perform the pull test at least three times for each combination of lever position and suit pressure conditions. The results from this study showed that as a whole (or in general), the subjects were able to pull on the lever at the back position with only about half the amount of force that they were able to exert on the lever at the front position. In addition, the results also showed that subjects wearing the pressurized suit were unable to reach the seat lever when it was located at the back. Furthermore, the pull forces on the front lever diminished about 50 % when subjects wore the pressurized suits. Based on these results from this study, it was recommended to NASA that the levers should not be located in the back position. In addition, further investigation is needed on whether the levers at the front of the seat could be modified or adjusted to increase the leverage for crew members wearing pressurized launch/escape suits.

Maida, J.↗

Material Model Parameters Optimization in Liquid Mercury Target Dynamics Simulation With Machine Learning Surrogates

A pulsed spallation target is subjected to very short (∼0.7μs) but intense loads (23.3 kJ) from repeated proton pulses, which knock away neutrons from the mercury atoms’ nuclei for a wide range application in physics, engineering, medicine, petroleum exploration, biology, chemistry, etc. The effect of this pulsed loading on the stainless-steel target module which contains the flowing mercury target material is difficult to predict not only due to its short but intense explosive-like physical reaction, but also the nonlinear material behavior of the liquid mercury in the structure. Injecting small helium bubbles in the mercury has been an efficient method of mitigating the pressure wave at high power level stage. However, prediction of the resultant loading on the target is more difficult when helium gas is intentionally injected into the mercury. A 2-phase material model that incorporates the Rayleigh-Plesset (R-P) model is expected to address this complex multi-physics dynamics problem by including the bubble dynamics in the liquid mercury. A parameter sensitivity study was firstly employed to understand their impact on the simulation strains. The investigated parameters included E, μ, γ, σ, n, VFgas, and gas cumulative volume curve control parameters a and b. Verification and validation results from sparse polynomial expansions (SPE) method and directional Gaussian smoothing (DGS) optimization show that the surrogate model had training error of ∼7% and validation error of ∼15%, indicating that machine learning methods and surrogate models can help optimize the uncertain parameters in the complex 2-phase material model. This approach is expected to fill the knowledge gap between unknown liquid-gas mixture material model and measured vessel strain responses.

Lin, Lianshan↗