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The random vibration forces between a payload and the sidewall of the space shuttle have been measured in flight and compared with the force specifications used in ground vibration tests. The flight data are in agreement with a semi-empirical method, which is widely used to predict vibration test force limits.
It has been demonstrated that current-generation global ocean general circulation models (OGCM) are able to simulate large-scale sea level variations fairly well. In this study, a GFDL/MOM-based OGCM was used to investigate its sensitivity to different wind forcing. Simulations of global sea level using wind forcing from the ERS-1 Scatterometer and the NMC operational analysis were compared to the observations made by the TOPEX/Poseidon (T/P) radar altimeter for a two-year period. The result of the study has demonstrated the sensitivity of the OGCM to the quality of wind forcing, as well as the synergistic use of two spaceborne sensors in advancing the study of wind-driven ocean dynamics.
The advent of triaxial, piezoelectric force gages and the associated signal processing is a precursor to several dynamics testing innovations. This new technology is applicable to spacecraft programs that JPL manages. An application of force measurement is force limiting (when testing spacecraft in random vibration tests). Base-drive and acoustic modal testing is a potential application.
Over the past few decades, the geographical distribution of emissions of substances that alter the atmospheric energy balance has changed due to economic growth and air pollution regulations. Here, we show the resulting changes to aerosol and ozone abundances and their radiative forcing using recently updated emission data for the period 1990-2015, as simulated by seven global atmospheric composition models. The models broadly reproduce large-scale changes in surface aerosol and ozone based on observations (e.g. 1 to 3 percent per year in aerosols over the USA and Europe). The global mean radiative forcing due to ozone and aerosol changes over the 1990-2015 period increased by 0.17 plus or minus 0.08 watts per square meter, with approximately one-third due to ozone. This increase is more strongly positive than that reported in IPCC AR5 (Intergovernmental Panel on Climate Change Fifth Assessment Report). The main reasons for the increased positive radiative forcing of aerosols over this period are the substantial reduction of global mean SO2 emissions, which is stronger in the new emission inventory compared to that used in the IPCC analysis, and higher black carbon emissions.
Hurricane Irma produced sustained hurricane force winds (lowest altitude occurrence at 54-ft) resulting in facility damage at Kennedy Space Center (KSC) on September 10-11, 2017. Irma's large destructive wind footprint also caused significant wind damage across the adjacent communities within Brevard County. Wind damage was augmented by frequent gusts of higher magnitude, along with several embedded tornadoes. Hurricanes have previously impacted and produced significant wind damage to infrastructure at KSC as a result of kinetic energy dissipated, in part, through contact with man-made structures. This paper is intended to provide information specific to the destructive force of Hurricane Irma's sustained winds and previous hurricanes of 2004, 2005 and 2016 as calculated from sustained 10 meters per second wind speeds measured from wind towers at KSC for the onset and cessation of destructive forces. Other factors such as pre-existing condition of impacted infrastructure, upstream structures causing turbulent wind patterns, and associated severe convective weather, are contributing factors but are not analyzed here.
The Earth’s climate is rapidly changing. Over the past centuries, aerosols, via their ability to absorb or scatter solar radiation and alter clouds, played an important role in counterbalancing some of the greenhouse gas (GHG) caused global warming. The multi-century anthropogenic aerosol cooling effect prevented present-day climate from reaching even higher surface air temperatures and subsequent more dramatic climate impacts. Trends in aerosol concentrations and optical depth show that in many polluted regions such as Europe and the United States of America, aerosol precursor emissions decreased back to levels of the 1950s. More recent polluting countries such as China may have reached a turning point in recent years as well, while India still follows an upward trend. Here we study aerosol trends in the CMIP6 simulations of the GISS ModelE2.1 climate model using a fully coupled atmosphere composition onfiguration, including interactive gas-phase chemistry, and either an aerosol microphysical (MATRIX) or a mass-based (OMA) aerosol module. Results show that whether global aerosol radiative forcing is already declining depends on the aerosol scheme used. Using the aerosol microphysical scheme, where the aerosol system reacts more strongly to the trend in sulfur dioxide (SO2) emissions, global peak direct aerosol forcing was reached in the 1980’s, whereas the mass-based scheme simulates peak direct aerosol forcing around 2010.
To better understand the atmospheric structure and dynamics on the Venus surface and provide input to climate models, there is a need to measure the wind velocity and direction on the surface and track changes over extended periods. A wind sensor based on a miniature drag-force anemometer is being developed to meet the challenges for wind measurements and operational requirements on the surface of Venus. The sensor materials are chosen to enhance durability and prevent reactivity with the Venus surface atmosphere. Advantages of this approach include that it is independent on variable heat transfer, has been matured in other harsh environment applications,and has a low mass and power requirement. This report describes demonstration of this miniature drag-force anemometer integrated with high temperature electronics in simulated Venus surface environment. Prototype drag-force anemometers were demonstrated integrated with an operational amplifier recording transient effects in a simulated Venus surface environment. For multidirectional wind monitoring, the sensors are small enough to be deployed orthogonally as a three-dimensional array on a small arm or mast
The two-degree-of-freedom system (TDFS) method used to derive force specifications for force limited vibration tests at JPL is reviewed and some of the limitations of the method and of the simple TDFS model are discussed. A new improved frequency shift force prediction method is developed and applied to a more complex model where the load and source have both residual and modal masses.
Based on the particle linear depolarization ratio (PLDR) and single-scattering albedo (SSA) values obtained for 1020 nm from Aerosol Robotic Network (AERONET) Version 3 Level 2.0 data collected in five regions, namely, northern China, Northwest Asia, the Tibetan Plateau, southern China and Southeast Asia, we classified seven types of aerosol (viz., purely dust, dust-dominated, pollution-dominated, non-absorbing [NA], weakly absorbing [WA], moderately absorbing [MA] and strongly absorbing [SA]) in order to assess the spatial and temporal distributions of their constituents and the radiative effects of their fine- and coarse-mode particles. The fine fraction dominated in northern China and also played a crucial role on the Tibetan Plateau and in southern China and Southeast Asia, whereas the coarse fraction prevailed in Northwest Asia. Furthermore, the fine-mode aerosol on the Tibetan Plateau exhibited its maximum radiative forcing efficiency (110.3 W m–2) during high concentrations of SA aerosol. Also, the lowest values for both the radiative forcing and the radiative forcing efficiency in southern China occurred during summer. Finally, the various aerosol constituents displayed distinct spatial and temporal distributions in Southeast Asia, with the SA aerosol contributing approximately 20% of the total aerosol on the Indochinese Peninsula and the NA and WA aerosol forming the largest percentages on the Malay Peninsula.
The National Force Measurement Technology Capability (NFMTC) is a nationwide partnership established in 2008 and sponsored by NASA’s Aeronautics Evaluation and Test Capabilities (AETC) project to maintain and further develop force and angle measurement capabilities primarily for NASA’s ground test facilities. One of the NFMTC’s primary objectives is to develop new force and angle measurement capabilities to meet the needs of researchers testing in NASA’s ground test facilities. This work will highlight several new capabilities that are either at or near operational readiness. A new six-component flow-through balance was designed and fabricated to support an upcoming retropropulsion test campaign at the NASA Langley Unitary Plan Wind Tunnel. The balance employs membranes in place of bellows, which have historically been used, and passes the flow through load bearing parts of the balance. Flow through the balance is optimized via the addition of flow guides, which are manufactured as separate parts, and attached to the balance. Calibration of this new flow-through balance demonstrates that it can suitably characterize the load and pressure ranges it was designed for, which provides aero researchers a new tool to directly measure retropropulsion performance of powered descent vehicles. Balances used in NASA’s ground test facilities are typically either single-piece balances or floating-frame balances. Historically, these two types of balances have generally used different front-end (model) attachments. Single-piece balances generally have a cylindrical front end that is forward of any measuring sections and at a reduced diameter relative to the balance outer diameter. Floating-frame balances generally have front end fits that extend over one or more measuring sections and that engage at the balance outer diameter. Recently, the NFMTC fabricated a single-piece balance with a front end fit that is compatible with the hardware used to calibrate floating-frame balances. Calibration results evaluating this front end fit will be presented. From a recent survey of angle measurement needs, the development of smaller angle measurement packages was identified as one area of improvement. Micro-electromechanical systems (MEMS) are continually being refined to provide high performance accelerometers that are a fraction of the volume of the quartz flexure based accelerometers that are standard in wind tunnels. A survey of commercial off-the-shelf MEMS accelerometers was conducted, and it identified the Safran Colibrys MS lines to be of adequate performance. Single-axis test boards and tri-axis rigid-flex production boards were designed and fabricated with a volume of approximately .18 cubic inches. The boards were designed to provide all the necessary conditioning for the MEMS accelerometers at levels to meet or exceed all requirements for the MS line sensors. Preliminary testing of these assembled sensor packages has demonstrated acceptable performance for wind-tunnel angle measurement. Several new rotating balances are at various stages of completion for NASA Glenn Research Center’s fan drive rigs. These balances provide direct measurement of thrust and torque of a driven fan or fan section to provide an estimate of fan efficiency and net thrust. Three two-component balances have been recently completed, and one six-component balance is in active development. A custom rotating telemetry system has been developed to support testing with these balances, and the telemetry system is integrated into the forward end of each one. The telemetry system is designed to remove mechanical sliprings by using an optical ethernet-based slipring for data transmission.
Anthropogenic aerosols (AERs) affect several aspects of the climate system across the world through radiative forcing and microphysical effects. These influences are particularly strong across South Asia, where AER concentrations are highest and further projected to increase in coming decades. Using large ensemble experiments from Earth system model, we examine how AERs shape the evolution of seasonal precipitation over South Asia inlate 20th century and 21st century climate in the presence of rising greenhouse gases (GHGs) concentrations. We find that AERs strongly reduce monsoon precipitation, moderately reduce post-monsoon precipitation, and negligibly influence pre-monsoon precipitation. Consequently, AERs delay the emergence of GHG-forced increases in precipitation by ~5 decades in the monsoon season and ~1 decade in the post-monsoon season. However, GHGs are projected to outpace the influence of AERs by mid 21st century, causing a steep intensification of monsoon and post-monsoon precipitation. We further show that local AERs have the strongest influence on precipitation in the monsoon and post monsoon seasons in the near-future (2020-2049). However, the contribution from remote AERs changes is also important in shaping the monsoon precipitation changes over northwestern South Asia. Further, the influence of local AERs monsoon precipitation remains stationary throughout the 21st century, indicating the insensitivity of relationship between local AOD and precipitation to the projected warming. A better understanding of aerosol-climate interactions and associated precipitation responses in is pertinent for policymakers to address the critical aspect of regional consequences over South Asia induced by externally forced climate change.
Light bosons can mediate long-range forces. We show that light bosonic mediators interacting with a background medium, in particular, with the cosmic neutrino background (CνB), may induce medium-dependent masses which could effectively screen long-range forces from detection. This leads to profound implications for long-range force searches in e.g. the Eöt-Wash, MICROSCOPE, and lunar laser-ranging (LLR) experiments. For instance, we find that when the coupling of the mediator to neutrinos is above 3 × 10 −10 or 5 × 10 −13 , bounds from LLR and experiments employing the Sun as an attractor, respectively, would be entirely eliminated. Larger values of the coupling can also substantially alleviate bounds from searches conducted at shorter distances.
Here, the accurate mapping of potential energy surfaces (PESs) is crucial to our understanding of the numerous physical and chemical processes mediated by atomic rearrangements, such as conformational changes and chemical reactions, and the thermodynamic and kinetic feasibility of these processes. Stochastic electronic structure theories, e.g., Quantum Monte Carlo (QMC) methods, enable highly accurate total energy calculations that in principle can be used to construct the PES. However, their stochastic nature poses a challenge to the computation and use of forces and Hessians, which are typically required in algorithms for minimum-energy pathway (MEP) and transition state (TS) identification, such as the nudged elastic band (NEB) algorithm and its climbing image formulation. Here, we present strategies that utilize the surrogate Hessian line-search method, previously developed for QMC structural optimization, to efficiently identify MEP and TS structures without requiring force calculations at the level of the stochastic electronic structure theory. By modifying the surrogate Hessian algorithm to operate in path-orthogonal subspaces and at saddle points, we show that it is possible to identify MEPs and TSs by using a force-free QMC approach. We demonstrate these strategies via two examples, the inversion of the ammonia (NH 3 ) molecule and the nucleophilic substitution (S N 2) reaction F – + CH 3 F → FCH 3 + F – . We validate our results using Density Functional Theory (DFT)- and Coupled Cluster (CCSD, CCSD(T))-based NEB calculations. We then introduce a hybrid DFT-QMC approach to compute thermodynamic and kinetic quantities, free energy differences, rate constants, and equilibrium constants that incorporates stochastically optimized structures and their energies, and show that this scheme improves upon DFT accuracy. Our methods generalize straightforwardly to other systems and other high-accuracy theories that similarly face challenges computing energy gradients, paving the way for highly accurate PES mapping, transition state determination, and thermodynamic and kinetic calculations at significantly reduced computational expense.
Radiolysis is a common approach to sterilize polymers, chemically modify them for upcycling, and accelerate their decomposition for recycling purposes. Reactive molecular dynamics (MD) simulations provide a powerful tool to generate atomic-level trajectories of the reactive processes and quantify radiolytic chemical degradation pathways. For this, machine learning (ML) surrogate models for reactive force fields with quantum mechanical accuracy are now widely used, which require ML training data sets that can provide information on atomic environments for target chemical systems. However, radiolysis chemistry can be highly complex and diverse, which poses significant challenges for generating training data to parametrize ML models. In this regard, we developed a method for optimizing the training data set using a cosine similarity metric to help guide training set selection for radiolysis of polyethylene, a model hydrocarbon polymer, as well as to enhance the transferability of our reactive ML force field (MLFF) to a variety of molecular and polymeric systems. Our approach performs atom-by-atom comparisons between local atomic environments to pinpoint important data points associated with rare and localized events, such as radiolysis damage within structures. We apply this approach to train the Chebyshev Interaction Model for Efficient Simulation (ChIMES) MLFF model, which expresses the atomic interaction potentials in terms of linear combinations of many-body Chebyshev polynomials. We first show that our method can reduce our training set size by ∼70% while improving overall accuracy compared to more standard MD model fitting approaches. We then validate our optimum model against diverse hydrocarbon simulation data, including simple alkanes and systems with unsaturated carbon bonds, over a wide range of thermodynamic conditions. Finally, we use our ChIMES model to perform MD simulations of radiolytic damage with large-scale systems that help avoid system size effects. Overall, our approach yields an MD force field that retains most of the accuracy of the underlying quantum method while yielding many orders of improvement in computational efficiency. In conclusion, our efforts will have impact on future hydrocarbon polymer radiolysis studies, where the chemical details of the polymer–radiation interactions can have a strong effect on the resulting products observed in experiments.
Fluid–silica interfaces are ubiquitous in chemistry, occurring in both natural geochemical environments and practical applications ranging from separations to catalysis. Simulations of these interfaces have been, and continue to be, a significant avenue for understanding their behavior. A constraining factor, however, is the availability of accurate force fields. Most simulations use traditional “mixing rules” to determine nonbonded dispersion interactions, an approach that has not been critically examined. Here, in this study, we present Lennard-Jones parameters for the interaction of carbon dioxide with silica interfaces that are optimized to reproduce density functional theory (DFT)-based binding energies. The modeling is based on the recently developed silica-DDEC force field, whose atomic charges are consistent with DFT calculations. Standard mixing rules are found to predict weaker CO 2 binding to silica than that obtained from DFT, an effect corrected by the optimized parameters given here. This behavior extends to other silica force fields (Clayff and Gulmen-Thompson), and the present Lennard-Jones parameters improve their performance as well. The effects of improved Lennard-Jones parameters on the structural and dynamical properties of condensed CO 2 in silica slit pores are also examined.
Ammonia (NH 3 ) is one of the most important industrial chemicals. The conventional NH 3 synthesis method-the Haber–Bosch process-converts atmospheric nitrogen (N 2 ) into NH 3 using H 2 with an iron (Fe) catalyst. However, this process requires high pressures (100–200 atm) and temperatures (700–800 K) near thermal equilibrium. Recently, Fe-based nanocatalysts have been reported to produce promising NH 3 yields under atmospheric pressures and temperature-modulated nonequilibrium conditions. Understanding the mechanism of nonequilibrium catalysis with programmed temperature variation could help to optimize this fully electrified and less energy-intensive process. Although reactive molecular dynamics (RMD) simulations can be a useful tool to model nonequilibrium catalytic processes, they require the development of accurate force fields (i.e., interatomic potentials). Here, we present a machine-learned (ML) force field within the Deep Potential MD (DPMD) framework, trained using periodic density functional theory (DFT) calculations, to model NH 3 synthesis on Fe catalysts with various surface adsorbates such as *N, *H, *N 2 , *H 2 , *NH, *NH 2 , and *NH 3 . Here, we generated the DFT data from static models of elementary reactions on the most stable (110) surface of body-centered cubic Fe, which then were augmented by data from constant number of particles–volume–temperature (NVT) DFT-MD trajectories at various temperatures. Finally, we utilized the fully optimized ML force field to investigate reaction dynamics at an Fe(110) surface at linearly increasing temperatures using NVT-DPMD simulations. Our simulations indicate that pulsed temperature ramping could prove favorable for NH3 synthesis. For example, we conducted ramping under multiple sets of conditions: (i) from 900 to 1200 K over periods of 0.1–0.3 ns for Fe surfaces precovered with N or NH along with H; and (ii) from 300 to 600 K over 0.1–0.3 ns for Fe surfaces precovered with NH 3 . While our simulations so far are limited to short time scales (very rapid heating), these observations shed light on the mechanism of the high NH 3 synthesis rate achieved in a novel temperature-modulated nonequilibrium catalytic reactor using pulsed heating and cooling.
Metal–organic frameworks (MOFs) offer promise as selective CO 2 sorbents, but successful MOF sorbent materials need high CO 2 binding affinity and selectivity for CO 2 over water. This work focuses on the use of machine-learned force fields (MLFFs) to model CO 2 adsorption in flexible MOFs, with a focus on SIFSIX-3-Cu, an anion-pillared MOF known for its high CO 2 affinity. A preliminary high-throughput screening of over 900 anion-pillared MOFs was performed using rigid UFF+DDEC6 force fields to predict zero-loading heats of adsorption for CO 2 and H 2 O. SIFSIX-3-Cu was selected for further computational study due to its predicted CO 2 heat of adsorption and experimental relevance. A DeePMD-based MLFF was trained to reproduce DFT (PBE+D3) energies and forces, with an iterative sampling scheme combining molecular dynamics, geometry optimization, random geometric insertion, and NVT Monte Carlo-based configuration generation to capture both attractive and repulsive regions of the potential energy surface. Flexibility of the MOF was explicitly included, contrasting with previous models that approximated the MOF as rigid. Hybrid Monte Carlo/molecular dynamics (MC/MD) simulations with the MLFF produced CO 2 adsorption isotherms in good agreement with experimental data at direct air capture (DAC) pressures (e.g., 40 Pa), in contrast to previous overestimations of CO 2 sorption by models with rigid structures. Bond and angle histogram analysis showed that MOF flexibility increased the variance of fluorine–fluorine diagonal distances at adsorption sites, resulting in a lower predicted sorption for flexible, asymmetric SIFSIX-3-Cu pore geometries compared to the rigid, symmetric DFT-optimized SIFSIX-3-Cu pore geometry. A detailed description of flexibility afforded by the MLFF resulted in an accurately predicted CO 2 uptake (0.88 mmol/g) at low pressure (40 Pa) compared to the experimentally measured value (1.24 mmol/g). In conclusion, these results underscore the importance of including framework flexibility when modeling adsorption phenomena in MOFs, particularly for low-pressure applications.
Here, we investigate the thermodynamic driving-force dependences of photoinduced charge separation (CS) and subsequent charge transfer dynamics in single-walled carbon nanotube (SWNT)–perylenediimide (PDI) donor–acceptor (D–A) superstructures. Pump–probe spectroscopy reveals that [SWNT (•+)n ]-(PDI –• ) n CS states form on an ∼100 fs time scale following photoexcitation; these dynamics are invariant across an ∼400 mV driving force range, indicating that SWNT hole polaron formation time scales are determined by nanotube lattice and solvent relaxation. These CS states feature SWNT hole polarons adjacent to (geminate) and nearby (nongeminate) PDI radical anions. Analysis of the free energy dependence for charge recombination (CR) of [SWNT •+ ] geminate -(PDI –• ) CS states highlights an ∼2 meV value for D–A electronic coupling (HAB) and ∼0.93 eV for the total reorganization energy (λ T ). A corresponding driving force dependence of the CR dynamics for [SWNT •+ ] nongeminate -(PDI –• ) CS states indicates a diminished H AB value (∼0.6 meV) and a larger λ T (∼1.1 eV), consistent with larger transfer distances. SWNT excitons that persist following photoinduced CS drive photooxidation of PDI –• components of [SWNT (•+)n ]-(PDI –• ) n CS states ( 1 SWNT* + PDI •– → PDI + SWNT •– ); this reaction manifests a significantly reduced λ T value (∼0.67 eV) as the initially prepared SWNT reduced state bears the character of a conduction band injected electron ([SWNT •– ] CB ). This reaction thus gives rise to relaxed, nongeminate SWNT electron and hole polarons on the same nanotube; these polarons react on a 10 2 ps time scale independent of the electronic structure of these SWNT-PDI superstructures.