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Investigation of Surface and Marine-Cloud Coupling and its Impact on Cloud Droplet Number Concentrations and Cloud Cover Over the Southern Ocean

The proposed work involves characterizing and quantifying both the thermodynamic and dynamical coupling of marine low clouds (MLC) with the sea surface using Atmospheric Radiation Measurement (ARM) observations during MARCUS field campaign and an LES model. ARM data from multiple sensors will be used (e.g., Doppler cloud radar, ceilometer, and microwave radiometer) to characterize the MLC-surface coupling by virtue of the vertical structure and integrated quantities of boundary-layer clouds, aerosols, as well as atmospheric profiles and surface meteorology. We have used a combination of case studies and statistics-based composite analyses to find any linkages between large-scale dynamics, MLC-surface coupling, and cloud and boundary layer properties, the sequence of which reflects the chain of causality. An LES model with explicit aerosol physics, which includes the cycle of aerosols by being consumed as CCN and be regenerated following cloud droplet evaporation, has been run to determine the sources and sinks of Nd and their dependence on the degree of MLC-surface coupling. We have examined the systematic differences in both Nd and cloud occurrence between the two clusters under different meteorological conditions and further examine their respective roles, as well as causal relationships by means of LES modeling. This study helped improve our understanding of the ACI by differentiating the dynamic role of the coupling and cloud physics denoted by Nd, bridging the linkage in the chain toward understanding mechanisms governing the persistence of MLC over the Southern Ocean, solving the long-lasting problem of the cloud cover underestimation over the SO by GCMs. Ample ARM data and LES model have been employed to achieve the objectives of the study.

54 ENVIRONMENTAL SCIENCES↗

Use of Interrupted Helium Flow in the Analysis of Vapor Samples with Flowing Atmospheric-Pressure Afterglow-Mass Spectrometry

The flowing atmospheric-pressure afterglow (FAPA) source was used for the mass-spectrometric analysis of vapor samples introduced between the source and mass spectrometer inlet. Through interrupted operation of the plasma-supporting helium flow, helium consumption is greatly reduced and dynamic gas behavior occurs that was characterized by schlieren imaging. Moreover, mass spectra acquired immediately after the onset of helium flow exhibit a signal spike before declining and ultimately reaching a steady level. This initial signal appears to be due to greater interaction of sample vapor with the afterglow of the source when helium flow resumes. In part, the initial spike in signal can be attributed to a pooling of analyte vapor in the absence of helium flow from the source. Finally, time-resolved schlieren imaging of the helium flow during on and off cycles provided insight into gas-flow patterns between the FAPA source and the MS inlet that were correlated with mass-spectral data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Photodissociation of methyl formate: Conical intersections, roaming and triple fragmentation

The photodissociation channels of methyl formate have been extensively investigated by two different advanced experimental techniques, ion imaging and Fourier-Transform-Infrared emission spectroscopy, combined with quantum chemical calculations and molecular dynamics simulations. Our aim is to characterize the role of alternative routes to the conventional transition-state mediated pathway: the roaming and the triple fragmentation processes. The photolysis experiments, carried out at a range of laser wavelengths in the vicinity of the triple fragmentation threshold, beside the simulation of large bunches of classical trajectories with different initial conditions, have shown that both mechanisms share a common path that involves a conical intersection during the relaxation process from the electronic excited state S{sub 1} to the ground state S{sub 0}.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A fast integrated mobility spectrometer for rapid measurement of sub-micrometer aerosol size distribution, Part II: Experimental characterization

A Fast Integrated Mobility Spectrometer (FIMS) with a wide dynamic size range has been developed for rapid aerosol size distribution measurements. The design and model evaluation of the FIMS are presented in the preceding paper (Paper I), and this paper focuses on the experimental characterization of the FIMS. Monodisperse aerosol with diameter ranging from 8 to 600 nm was generated using Differential Mobility Analyzer (DMA), and was measured by the FIMS in parallel with a Condensation Particle Counter (CPC). The mean particle diameter measured by the FIMS is in good agreement with the DMA centroid diameter. Comparison of the particle concentrations measured by the FIMS and CPC indicates the FIMS detection efficiency is essentially 100% for particles with diameters of 8 nm or larger. For particles smaller than 20 nm or larger than 200 nm, FIMS transfer function and resolution can be well represented by the calculated ones based on simulated particle trajectories in the FIMS. For particles between 20 and 200 nm, the FIMS transfer function is boarder than the calculated, likely due to non-ideality of the electric field, including edge effects near the end of the electrode, which are not represented by the 2-D electric field used to simulate particle trajectories.

54 ENVIRONMENTAL SCIENCES↗

NeuroSEM: A hybrid framework for simulating multiphysics problems by coupling PINNs and spectral elements

Multiphysics problems that are characterized by complex interactions among fluid dynamics, heat transfer, structural mechanics, and electromagnetics, are inherently challenging due to their coupled nature. While experimental data on certain state variables may be available, integrating these data with numerical solvers remains a significant challenge. Physics-informed neural networks (PINNs) have shown promising results in various engineering disciplines, particularly in handling noisy data and solving inverse problems in partial differential equations (PDEs). However, their effectiveness in forecasting nonlinear phenomena in multiphysics regimes, particularly involving turbulence, is yet to be fully established. Here, this study introduces NeuroSEM, a hybrid framework integrating PINNs with the highfidelity Spectral Element Method (SEM) solver, Nektar++. NeuroSEM leverages the strengths of both PINNs and SEM, providing robust solutions for multiphysics problems. PINNs are trained to assimilate data and model physical phenomena in specific subdomains, which are then integrated into the Nektar++ solver. We demonstrate the efficiency and accuracy of NeuroSEM for thermal convection in cavity flow and flow past a cylinder. The framework effectively handles data assimilation by addressing those subdomains and state variables where the data is available. We applied NeuroSEM to the Rayleigh-B´enard convection system, including cases with missing thermal boundary conditions and noisy datasets. Finally, we applied the proposed NeuroSEM framework to real particle image velocimetry (PIV) data to capture flow patterns characterized by horseshoe vortical structures. Our results indicate that NeuroSEM accurately models the physical phenomena and assimilates the data within the specified subdomains. The framework’s plug-and-play nature facilitates its extension to other multiphysics or multiscale problems. Furthermore, NeuroSEM is optimized for efficient execution on emerging integrated GPU-CPU architectures. This hybrid approach enhances the accuracy and efficiency of simulations, making it a powerful tool for tackling complex engineering challenges in various scientific domains.

42 ENGINEERING↗

Experimental Characterization of an Electric Ducted Fan for the SUSAN 25% Scale Research Vehicle

An electric ducted fan (EDF) was tested in the NASA Langley 12-Foot Low-Speed Tunnel for the SUbsonic Single Aft eNgine (SUSAN) Electrofan 25% scale research vehicle, which incorporates distributed electric fans along the wings and serves as a scaled electrified transport aircraft testbed. The commercial-off-the-shelf EDF was selected as a propulsor that can meet the 25% scale vehicle geometry constraints, along with the performance requirements throughout the flight profile. The test included a series of one-factor-at-a-time (OFAT) and design of experiments (DOE) approaches that were implemented across a range of fan speed, voltage, freestream dynamic pressure, and incidence angle settings to characterize the performance of the EDF. Several test matrix designs and modeling approaches were considered. System identification methods were used to develop a static motor model, a dynamic motor model, an EDF thrust model, and a power consumption model. The model predictive capabilities were then evaluated with validation data not used in the modeling process. The results provide a comprehensive set of models developed to characterize the fan, and offer general insight into EDF modeling approaches.

electric ducted fan↗

Recurrence quantification analysis of simulations of near-marginal dissipative-trapped-electron-mode turbulence

Recurrence quantification analysis (RQA) is a powerful tool to study dynamical systems and to help us understand and characterize the underlying physics when a transition occurs. The idea is based on the fact that, given sufficiently long time lapses, every dynamical system returns to states arbitrarily close to those it had in the past. This fundamental property of dynamical systems is called recurrence. In this work, we analyze, using the RQA technique, the recurrence properties of time series obtained from a series of numerical simulations of a dissipative-trapped-electron-mode (DTEM) turbulence model in near-marginal conditions where a transition in the nature of turbulent transport was observed as a subdominant diffusive channel strength is increased from zero [J. A. Mier et al., Phys. Plasmas 15, 112301 (2008)]. The results of the RQA analysis clearly show that the degree of determinism and complexity of the dynamics closely follows the degree of non-diffusiveness in the observed transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Inferred Sea Level Prediction in the NASA GMAO Seasonal Forecasting System

Reliable predictions of sea level anomalies on seasonal timescales with lead times of 1 to 9 months may have relevance to stakeholders – for example, in the advance deployment of resources for coastal flood mitigation. Routine prediction and analysis may also highlight physical processes associated with sea level change and modeling capabilities on seasonal and other timescales. These forecasts may represent interannual changes in the seasonal slope of the ocean surface, teleconnection effects such as the El Niño/Southern Oscillation phenomenon, and variations in seasonal hydrology including precipitation and coastal runoff. Coupled atmosphere/ocean models are routinely used in the seasonal prediction of temperature anomalies, precipitation anomalies, sea ice cover, and climate indices such as the Niño3.4 predictions under the North American Multi-Model Ensemble (NMME) protocol. Within the limits of their configuration, these complex Earth-system models have a potential for depicting regional changes in oceanic column properties, including the sea surface height. Seasonal prediction models generally have no representation of long-term mass contributions from melting land ice, or changes in vertical land motion; their output may be more specifically characterized as predictions of the ocean dynamic sea level. In practice however, the sea surface height prognostic variable is substantially compromised by the forecast model response to initial conditions. Imbalances between the initial, observed hydrologic cycle and the forecast model state produce abrupt adjustments in the model sea surface height. As a result, most seasonal prediction systems employ a constraint on the globally-averaged sea surface height that is applied at each time step. This essentially renders the prognostic sea surface height variable as unserviceable. Several approaches have previously been used to retrieve sea level information from seasonal forecasts beyond the use of the sea surface height variable. Here, we extend a method of relating other prognostic values, including ocean circulation and climate indices, to observed sea level variations. We use the merged altimetry record of the NASA MEaSUREs Gridded Sea Surface Height Anomalies data set and monthly revised local reference gauge observations from the National Oceanography Centre Permanent Service for Mean Sea Level (PSMSL) to evaluate derived prognostic variables from the NASA Global Modeling and Assimilation Office subseasonal-to-seasonal system version 2.1 (GMAO S2S v2.1). We focus on results for the midlatitudes with particular emphasis on US gauge locations. As shown in previous studies, prognostic ENSO-related indices in boreal winter are well correlated with gauge observations for the US west coast, but also for other locations in the southeastern US. Other forecast climate indices such as the North Atlantic Oscillation have relations to sea level that are limited both seasonally and spatially. As expected, surface atmospheric pressure (e.g., inverse barometer effect) is found to be particularly well correlated with observed sea level. We provide a characterization of forecast skill for seasonal sea level with this method.

Richard I Cullather↗

WRAP-RIB antenna technology development

The wrap-rib deployable antenna concept development is based on a combination of hardware development and testing along with extensive supporting analysis. The proof-of-concept hardware models are large in size so they will address the same basic problems associated with the design fabrication, assembly and test as the full-scale systems which were selected to be 100 meters at the beginning of the program. The hardware evaluation program consists of functional performance tests, design verification tests and analytical model verification tests. Functional testing consists of kinematic deployment, mesh management and verification of mechanical packaging efficiencies. Design verification consists of rib contour precision measurement, rib cross-section variation evaluation, rib materials characterizations and manufacturing imperfections assessment. Analytical model verification and refinement include mesh stiffness measurement, rib static and dynamic testing, mass measurement, and rib cross-section characterization. This concept was considered for a number of potential applications that include mobile communications, VLBI, and aircraft surveillance. In fact, baseline system configurations were developed by JPL, using the appropriate wrap-rib antenna, for all three classes of applications.

Freeland, R. E.↗

Dynamical Threshold of Diluteness of Soft Colloids

The dynamics of soft colloids in solutions is characterized by internal collective motion as well as center-of-mass diffusion. Using neutron scattering we demonstrate that the competition between the relaxation processes associated with these two degrees of freedom results in strong dependence of dynamics and structure on colloid concentration, c, well below the overlap concentration c*. Triggered by the increasing inter-particle collisions, substantial structural dehydration and slowing-down of internal dynamics occurs before geometrically defined colloidal overlap develops. This observation is surprising since it is generally believed that the internal dynamics and conformation of soft colloidal particles essentially remain invariant below c*. The competition between these two relaxation processes gives rise to a new dynamically-defined dilute threshold concentration well below c*.

Chen, Wei-Ren↗

Characterization of Gramicidin A in Triblock and Diblock Polymersomes and Hybrid Vesicles via Continuous Wave Electron Paramagnetic Resonance Spectroscopy

Studying membrane proteins in a native environment is crucial to understanding their structural and/or functional studies. Often, widely accepted mimetic systems have limitations that prevent the study of some membrane proteins. Micelles, bicelles, and liposomes are common biomimetic systems but have problems with membrane compatibility, limited lipid composition, and heterogeneity. To overcome these limitations, polymersomes and hybrid vesicles have become popular alternatives. Polymersomes form from amphiphilic triblock or diblock copolymers and are considered more robust than liposomes. Hybrid vesicles are a combination of lipids and block copolymers that form vesicles composed of a mixture of the two. These hybrid vesicles are appealing because they have the native lipid environment of bilayers but also the stability and customizability of polymersomes. Gramicidin A was incorporated into these polymersomes and characterized using continuous wave electron paramagnetic resonance (CW-EPR) and transmission electron microscopy (TEM). EPR spectroscopy is a powerful biophysical technique used to study the structure and dynamic properties of membrane proteins in their native environment. Spectroscopic studies of gramicidin A have been limited to liposomes; in this study, the membrane peptide is studied in both polymersomes and hybrid vesicles using CW-EPR spectroscopy. Lineshape analysis of spin-labeled gramicidin A revealed linewidth broadening, suggesting that the thicker polymersome membranes restrict the motion of the spin label more when compared to liposome membranes. Statement of Significance: Understanding membrane proteins’ structures and functions is critical in the study of many diseases. In order to study them in a native environment, membrane mimetics must be developed that can be suitable for obtaining superior biophysical data quality to characterize structural dynamics while maintaining their native functions and structures. Many currently widely accepted methods have limitations, such as a loss of native structure and function, heterogeneous vesicle formation, restricted lipid types for the vesicle formation for many proteins, and experimental artifacts, which leaves rooms for the development of new biomembrane mimetics. The triblock and diblock polymersomes and hybrid versicles utilized in this study may overcome these limitations and provide the stability and customizability of polymersomes, keeping the biocompatibility and functionality of liposomes for EPR studies of membrane proteins.

59 BASIC BIOLOGICAL SCIENCES↗

Simulation Analysis of the Temperature Dependence of Lignin Structure and Dynamics

Lignins are hydrophobic, branched polymers that regulate water conduction and provide protection against chemical and biological degradation in plant cell walls. Lignins also form a residual barrier to effective hydrolysis of plant biomass pretreated at elevated temperatures in cellulosic ethanol production. Here, the temperature-dependent structure and dynamics of individual softwood lignin polymers in aqueous solution are examined using extensive (17 s) molecular dynamics simulations. With decreasing temperature the lignins are found to transition from mobile, extended to glassy, compact states. The polymers are composed of blobs, inside which the radius of gyration of a polymer segment is a power-law function of the number of monomers comprising it. In the low temperature states the blobs are interpermeable, the polymer does not conform to Zimm/Stockmayer theory, and branching does not lead to reduction of the polymer size, the radius of gyration being instead determined by shape anisotropy. At high temperatures the blobs become spatially separated leading to a fractal crumpled globule form. The low-temperature collapse is thermodynamically driven by the increase of the translational entropy and density fluctuations of water molecules removed from the hydration shell, thus distinguishing lignin collapse from enthalpically driven coil globule polymer transitions and providing a thermodynamic role of hydration water density fluctuations in driving hydrophobic polymer collapse. Although hydrophobic, lignin is wetted, leading to locally enhanced chain dynamics of solvent-exposed monomers. The detailed characterization obtained here provides insight at atomic detail into processes relevant to biomass pretreatment for cellulosic ethanol production and general polymer coil globule transition phenomena.

Petridis, Loukas↗

Machine Intelligence-Centered System for Automated Characterization of Functional Materials and Interfaces

Classic design of experiment relies on a time-intensive workflow that requires planning, data interpretation, and hypothesis building by experienced researchers. Here, in this paper, we describe an integrated, machine-intelligent experimental system which enables simultaneous dynamic tests of electrical, optical, gravimetric, and viscoelastic properties of materials under a programmable dynamic environment. Specially designed software controls the experiment and performs on-the-fly extensive data analysis and dynamic modeling, real-time iterative feedback for dynamic control of experimental conditions, and rapid visualization of experimental results. The system operates with minimal human intervention and enables time-efficient characterization of complex dynamic multifunctional environmental responses of materials with simultaneous data processing and analytics. The system provides a viable platform for artificial intelligence (AI)-centered material characterization, which, when coupled with an AI-controlled synthesis system, could lead to accelerated discovery of multifunctional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

On the Use of a Driven Wedge Test to Acquire Dynamic Fracture Energies of Bonded Beam Specimens

A driven wedge test is used to characterize the mode I fracture resistance of adhesively bonded composite beam specimens over a range of crosshead rates up to 1 m/s. The shorter moment arms (between wedge contact and crack tip) significantly reduce inertial effects and stored energy in the debonded adherends, when compared with conventional means of testing double cantilever beam (DCB) specimens. This permitted collecting an order of magnitude more crack initiation events per specimen than could be obtained with end-loaded DCB specimens bonded with an epoxy exhibiting significant stick-slip behavior. The localized contact of the wedge with the adherends limits the amount of both elastic and kinetic energy, significantly reduces crack advance during slip events, and facilitates higher resolution imaging of the fracture zone with high speed imaging. The method appears to work well under both quasi-static and high rate loading, consistently providing substantially more discrete fracture events for specimens exhibiting pronounced stick-slip failures. Deflections associated with beam transverse shear and root rotation for the shorter beams were not negligible, so simple beam theory was inadequate for obtaining qualitative fracture energies. Finite element analysis of the specimens, however, showed that fracture energies were in good agreement with values obtained from traditional DCB tests. The method holds promise for use in dynamic testing and for characterizing bonded or laminated materials exhibiting significant stick slip behavior, reducing the number of specimens required to characterize a sufficient number of fracture events.

36 MATERIALS SCIENCE↗

Groundwater flowpath characteristics drive variability in per- and polyfluoroalkyl substances (PFAS) loading across a stream-wetland system

Groundwater dependent ecosystems in areas with industrial and military land use are at risk of direct exposure to a wide range of contaminants, including PFAS chemicals. Glaciated terrain often has mixed high and low permeability sediments coupled with groundwater flow-through lake features. These hydrogeologic attributes create highly complex ‘source to seep’ dynamics that make spatiotemporal contaminant transport patterns difficult to predict. We investigated one such system in detail using a suite of heat-tracing and chemical methods. Numerous (n=57) preferential groundwater discharge zones (vertical flux rates ranging 0.2 to 3.2 m/d) were identified across the upper Quashnet River stream-wetland system in Mashpee, MA, USA, adjacent to an Air Force Base with several known PFAS source areas. Surface-water and groundwater samples were collected and analyzed (n=145) for precursors and terminal PFAS compounds between March and September 2022. Samples were collected at identified seeps along the Quashnet River (n=59), from wells upgradient from the stream-wetland system (n= 44), from contributing flow-through kettle lakes (n=8), and at multiple locations along the Quashnet River (n=34). Samples from seeps and wells had measured PFAS concentrations ranging from non-detect to approximate 3,500 ng/L (mean= 1,650 ng/L), and a range of deuterium excess values (3.2 to 15.9 per mil) indicative of varying degrees of groundwater-lake interaction prior to emergence at the discharge zones. Groundwater-lake interaction along flowpaths that sourced the sampled seeps was farther supported by significant correlations (p < 0.01) between deuterium excess and %PFAS precursors, and between %PFAS precursors and multiple terminal PFAS compounds (e.g., PFPeS, PFBS, PFHxS). However, some sampled seeps contributing groundwater to the stream-wetland system had much higher total PFAS concentrations (>1000 ng/L) than the upgradient kettle lakes, despite showing lake (evaporative) isotopic signatures, indicating the potential for groundwater flowpath convergence at wetland discharge zones and the influence of lakebed PFAS precursor reactions. PFAS compounds and water isotopic composition at sampled multilevel groundwater wells, rivers, lakes, and seeps suggest that a complex mixture of source groundwater and flowpath characteristics are responsible for diverse observed PFAS mixtures at preferential discharge zones across the stream-wetland system. Further, total PFAS loading patterns to the Quashnet River via groundwater discharge remained remarkably similar from winter to summer to fall conditions, despite a regional dry period in late summer 2022 with the upper river channel completely drying. This work addresses gaps in the existing PFAS literature by demonstrating the importance of subsurface fate and transport on PFAS compound concentrations in controlling contaminant mass loading in preferential groundwater discharge zones and presents a transferrable field toolkit for efficient characterization of spatially preferential PFAS transport dynamics.

Contaminant transport↗

Atomic structure and grain shape evolution of nanodiamond during annealing in oxidizing atmosphere from neutron diffraction and MD simulations

In this work, real space pair-distribution function (PDF) analysis in conjunction with molecular dynamics (MD) simulations was applied to characterize crystal structure, shape and surface structure of diamond nanoparticles annealed in air up to 880 °C. MD simulated models of individual nanodiamond particles of various shapes and sizes were used to calculate theoretical radial distribution functions G(r) for powders with different grain size distributions. The calculated curves, showing distinct differences for the explored parameter space, were compared to the experimental G(r) functions obtained from neutron scattering for annealed detonated nanodiamond samples in a search for a model best describing the actual powders. It was found that as-synthesized nanodiamond grains are terminated by equally abundant (100), (110) and (111) crystallographic faces and their structure does not change upon annealing in air up to 280 °C. The shape and size of grains annealed above 480 °C changes due to surface etching. The etching rate differs between crystals faces and depends on temperature, resulting in the observed differences in grain shape. Below 680 °C the share of the (110) facets gradually increases and at 680 °C the grains become rhombic dodecahedra terminated solely by (110) surfaces. Further increase of the annealing temperature promotes formation of (111) surfaces and at 880 °C the preferred grain shape becomes an octahedron terminated by a variant of (111) surfaces possessing three dangling sp3 bonds per atom. At lower temperatures all grains become smaller and the size distribution moves towards the lower values. Furthermore, as the annealing temperature increases, the smallest grains disappear entirely and the average grain size grows back.

36 MATERIALS SCIENCE↗

Solid-State NMR Investigations of Carbon Dioxide Gas in Metal–Organic Frameworks: Insights into Molecular Motion and Adsorptive Behavior

Solid-state nuclear magnetic resonance (SSNMR) methods have been routinely used for the characterization of both the structure and the dynamics of metal organic frameworks (MOFs), a collection of porous media investigated for potential applications in carbon capture technologies, selective separation of small molecules, and catalysis.(1) The use and development of SSNMR techniques that enable the nondestructive characterization of the adsorbed behavior have become essential steps in bettering our understanding of MOFs and are often complementary to traditional methods of structural characterization. This Review aims to give a brief introduction to the relevant concepts of SSNMR and the methods employed when investigating the phenomenon of adsorbed carbon dioxide gas in MOFs. We summarize the published SSNMR literature on CO2 in MOFs, as well as highlight the best experimental practices when working with these complex systems.

membrane, carbon capture, materials and chemistry ↗

Comparison of Pre- and Post-Flight Estimations of Pitch Damping Coefficients for Unguided Entry Vehicles

Introduction: Pre-flight predictions of pitch damping coefficient (𝐶!!+𝐶!"̇)curves are used in entry simulations to determine flight readiness and if any dynamic remediation strategies are required. Accurate characterization of these pitch damping coefficient curves is crucial for mission success. Historically, pre-flight estimations of these curves are derived experimentally either via ballistic range testing or with 1-degree-of-freedom (DOF) free-or forced-oscillation wind tunnel testing. Methodology:With post-flight best-estimated trajectories, a fitting procedure as described in Karlgaard, et. al. [1] is used to compare pre-and post-flight pitch damping coefficients. This technique relies on an assumed analytical form of the trajectory, a limited 3-DOF representation described in Schoenenbergerand Queen [2], which results in anEuler-Cauchy solution form.This solution assumes constant density,thus limited amplitude multi-peak windows of the trajectory are considered to populate the pitch damping-amplitudes pace. Fig. 1 shows preliminary estimations of the pitch damping coefficients estimated using the post-flight best estimated trajectoryfor MER B, using a3-amplitude-peak window. Important to note is that the Euler-Cauchy solution also assumes planar motion, thus coning or 𝛽contribution is not included. Further,the estimated post-flight pitch damping approximations and the pre-flight predictions shown are effective representations of pitch damping, or the integrated effect of the pitch damping coefficient over one pitch cycle at the corresponding cycle’s peak amplitude. Effective pitch damping coefficient curves provide more intuitive insights about where the vehicle is stable and permits readily processed comparisons between data-sets. It is important to note that most pitch damping curves, such as those reported in aerodatabases and utilized in flight mechanics trajectory simulations, are represented in instantaneous angle-of-attack space distinct from what is presented in Fig 1. The extracted post-flight pitch damping coefficient points show a wide range of values across a narrow band of amplitudes (Fig.1a), albeit centered on the published pre-flight approximation. This also applies to the prediction as a function of Mach in Fig1b, where the post-flight scatter points are centered around the pre-flight predictions, but the pre-flight predictions notably lack data aboveMach 5.Further tuning of the technique, such as changing the number of peaks considered in each stencil, resolving density in higher resolution, and employing more accurate fitting procedures (beyond scipy.curve_fit()), will be performed. PosterFocus:This study will apply this reconstruction method to the as-flown trajectories for the following unguided entry vehicles: MER A, MER B, IRVE3, Phoenix, Insight, Pathfinder, and SIAD. The pitch damping coefficient will be derived from these trajectories and compared with the pre-flight predictions. Comparing across different missions, entry environments, and vehicle geometries can inform where our pre-flight testing methodologies accurately capture the flight dynamics. Results will provide valuable insight into the accuracy of pre-flight predicted pitch damping curves. Beyond that, this method can shed light on how accurate these curves need to be, which can inform uncertainty ranges applied to pre-flight curves for other missions.

pitch damping coefficient↗

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