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At least 235 records · Page 13

Characterization of partially observed epidemics through Bayesian inference: application to COVID-19

We demonstrate a Bayesian method for the "real-time'" characterization and forecasting of partially observed COVID-19 epidemic. Characterization is the estimation of infection spread parameters using daily counts of symptomatic patients.The method is designed to help guide medical resource allocation in the early epoch of the outbreak. The estimation problem is posed as one of Bayesian inference and solved using a Markov chain Monte Carlo technique. The data used in this study was sourced before the arrival of the second wave of infection in July 2020. The proposed modeling approach, when applied at the country level, generally provides accurate forecasts at the regional, state and country level. The epidemiological model detected the flattening of the curve in California, after public health measures were instituted.The method also detected different disease dynamics when applied to specific region of New Mexico

60 APPLIED LIFE SCIENCES↗

Frequency domain approach for evaluation of stochastic control of elastic spacecraft

An attempt is made to develop a reduced-order filter for an elastic spacecraft. The frequency-domain approach is resorted to both for arriving at an appropriate ROF and for evaluating the resulting stochastic flight controller. The frequency-domain approach employed is contrasted to the time-domain approach previously utilized by the authors. A linearized deterministic dynamical model of a solar electric propulsion spacecraft is analyzed. Flexibility modes were incorporated profitably into the ROF model, and the stochastic controllers exhibit notching of structural resonances reminiscent of classical notch filters. Accurate estimates of modal parameters (damping, natural frequency) are deemed crucial, and use of worst-case values in the ROF design is recommended.

Larson, V.↗

Ultrawideband asynchronous tracking system and method

A passive tracking system is provided with a plurality of ultrawideband (UWB) receivers that is asynchronous with respect to a UWB transmitter. A geometry of the tracking system may utilize a plurality of clusters with each cluster comprising a plurality of antennas. Time Difference of Arrival (TDOA) may be determined for the antennas in each cluster and utilized to determine Angle of Arrival (AOA) based on a far field assumption regarding the geometry. Parallel software communication sockets may be established with each of the plurality of UWB receivers. Transfer of waveform data may be processed by alternately receiving packets of waveform data from each UWB receiver. Cross Correlation Peak Detection (CCPD) is utilized to estimate TDOA information to reduce errors in a noisy, multipath environment.

Arndt, G. Dickey↗

Simulation of Energetic Neutral Atoms from Solar Energetic Particles

Energetic neutral atoms (ENAs) provide the only way to observe the acceleration site of coronal-mass-ejection-driven (CME-driven) shock-accelerated solar energetic particles (SEPs). In gradual SEP events, energetic protons can charge exchange with the ambient solar wind or interstellar neutrals to become ENAs. Assuming a CME-driven shock with a constant speed of 1800 km/s and compression ratio of 3.5, propagating from 1.5 to 40 Rs, we calculate the accelerated SEPs at 5-5000 keV and the resulting ENAs via various charge-exchange interactions. Taking into account the ENA losses in the interplanetary medium, we obtain the flux-time profiles of these solar ENAs reaching 1AU.We find that the arriving ENAs at energies above approx.100 keV show a sharply peaked flux-time profile, mainly originating from the shock source below 5 RS, whereas the ENAs below approx. 20 keV have a flat-top time profile, mostly originating from the source beyond 10 Rs. Assuming the accelerated protons are effectively trapped downstream of the shock, we can reproduce the STEREO ENA fluence observations at approx. 2-5 MeV/nucleon. We also estimate the flux of ENAs coming from the charge exchange of energetic storm protons, accelerated by the fast CME-driven shock near 1AU, with interstellar hydrogen and helium. Our results suggest that appropriate instrumentation would be able to detect ENAs from SEPs and to even make ENA images of SEPs at energies above approx.10-20 keV.

sun↗

Lander Lighting Solution to Reduce Pilot & Autonomous Approach Errors

The south pole lighting environment will have harsh low inclination sunlight, making overhead judgement of surface features difficult. Autonomous solutions are great, however, the need for visual monitoring and independent go/no-go decisions remain. Our project proposes that lunar landing systems will be better served by including a powerful landing light system that improves visibility of surfaces from overhead by illuminating the ground at critical distances for the crew to make last minute decisions regarding an approach. The project utilized computer-based optical modeling software to predict requirements for a potential landing light system. The analysis based the lamp prediction from commercially available LED chip sets and lamp optics. The goal was to illustrate a method to raise the surface contrast of a landing site within an acceptable contrast threshold for most camera systems and human observers to recognize hazards that would not be noticed with low inclination sunlight alone. The Apollo lunar landings benefitted from overhead sun or dark conditions. The surface lighting at the Lunar South Pole is a harsh environment where surfaces are lit from a low inclination angle by the sun (from the side). This change in lighting condition precipitates a need for updated lunar landing systems that facilitate improved recognition of landing sites, and thereby increase pilot awareness of landing hazards. The reliance on LIDAR and other autonomous mechanisms alone is risky given the known usage of visual monitoring for operator concurrence on current spacecraft programs and present-day autonomous land-based vehicles. Visual monitoring via cameras or windows requires the surface contrast to be within 3 orders of magnitude for reasonable recognition of objects. Artificial overhead illumination, when sufficiently sized, provides a means to even out contrast problems created by low inclination sunlight, potentially reducing piloting errors. Current vehicle requirements do not specify this type of guidance for the purpose of increasing mission success. An optical ray-trace simulation model was developed in Zemax Optics Studio to predict the best combination of LED power, LED optics, lamp quantity, and lamp location to raise the surface contrast to within 2 orders of magnitude from 3 orders required to further increased visibility and reduce risk. The project considered the following design constraints: potential base diameter of lander, approach distance(s) for a go-no-go decision point (200 meter), solar inclination angle (2-7), lunar surface reflectance (10%), LED chip sets, LED focusing optics, LED power, lamp quantity, lamp locations, and illumination diameter of lunar surface landing zone. The results can be used to establish minimum design constraints for vehicle landing light systems. With a solar inclination angle ranging from 2-7 degrees, the horizontal illumination of the lunar surface is attenuated by about 10% when compared to overhead illumination from the Sun. This modifies the sun's maximum of 130,000 lux to 13,000 lux horizontal illuminance. The artificial lighting system was designed to provide an 18-meter-wide illumination zone, to create viewing clearances around a 6-meter-wide lander. The system provides an average illuminance of 300 lux, meeting the 2 orders of magnitude criteria. The solution utilized modern Chip On Board LEDs, that each utilized 17 watts, with focusing Total Internal Reflection (TIR) lenses. A lighting system of 300 LEDs was arrayed along the "bottom" of a “lander”. With 17 watts per LED, the system is estimated to require 5100 watts. This is a large amount of power, but it would only be needed during critical phases during the landing. LED lighting systems can be dimmed, and it is assumed that as the lander arrives closer to the landing site, the lighting system power can be adjusted as needed to produce the necessary surface illuminance. The designed reduction of contrast improves reliability of safety assessments using real time visible light camera systems and out the window viewing by the crew.

T A Clark↗

Thermal Protection System to Enable Ice Giant Aerocapture Mission for Delivering Both an Orbiter and an In Situ Probe

The Ice Giants have been identified as high priority science destinations in the last Decadal Survey [1] and could benefit from aerocapture as the primary method for orbit insertion [2]. A mass-efficient aerocapture system will enable the delivery of an orbiter along with an atmospheric probe (for in situ measurements to anchor global data collected by the orbiter) and possibly a lander at Triton [3]. Aerocapture could be executed either using low L/D rigid aeroshell with lift modulation (LMA) [4] or using deployable aeroshell using drag modulation (DMA) [3]. Nearly two decades ago, a NASA-funded team performed Neptune-Triton aerocapture studies with a mid-L/D lifting configuration [5] for achieving orbit using LMA. This study showed aerocapture challenges. Due to very high peak entry conditions combined with very high heat-load, a suite of TPS materials was required and this suite was deemed problematic from a qualification perspective, due test facility limitations. In the past 20 years, progress made in GN&C for lift-guided entry missions such as MSL, Orion EFT1, Mars 2020 and the upcoming Artemis missions, and the expertise in blunt body aerodynamics at large scale (~ 5m) has led the EDL community to conclude that aerocapture is a “go do” engineering activity and most technologies are in hand to propose missions with aerocapture [6] [7]. Aerocapture using DMA, currently in development, is an option for Ice Giant Missions. While DMA is simpler in some sense, due to ballistic entry and no need for lift-guided maneuvering, it has challenges and it’s maturity is lower. LMA and DMA both require one or more ablative Thermal Protection System (TPS) materials for the rigid aeroshell element. The ablative TPS needs to be robust and mass efficient due to the high heat loads and size of the rigid aeroshell. Currently, there are capable ablative thermal protection materials, e.g., Heatshield for Extreme Entry Environments Technology (HEEET), 3-D woven Mid-Density Carbon- Phenolic (3MDCP), and PICA (Phenolic-Impregnated Carbon Ablator) that are mature, i.e., at TRL 6 or higher. NASA also invested in Conformal PICA that was matured to TRL 5. Our goal is to evaluate the applicability of high TRL TPS and consider other design options. We first establish bounding aerocapture trajectories for a wide range of arrival conditions and the associated aerothermal environment. Based on the environments, we then determine the predicted TPS mass for the aeroshell [4]. In this presentation, we will outline the process by which we establish bounding aerocapture trajectories for hyperbolic excess velocities ranging from 27 km/s to 35 km/s, which are shown to be a range of velocities that can reduce the trip time from ~14 years to 8 years. The above velocity range translates to ~12 km/s to ~24 km/s arrival velocities at the planetary entry interface [2]. The velocity reduction required to achieve orbit ranges between ~2.5 km/s to 9.5 km/s for both Neptune and Triton. Propulsive insertion alone, due to the amount of fuel required to achieve the required velocity reduction, limits the science returned [2]. We establish the bounding aerocapture trajectories for a low L/D (~ 0.4) configuration for three different ballistic coefficients. The ballistic coefficient range is determined from three different aeroshell diameters of 3m, 4m and 5m and with an entry system mass of 2200 kg. With the above range of design parameters, we then determine conservative/bounding estimates of aerothermal environments by using a combination of CFD simulations and stagnation point heating estimates [7]. This engineering approach allows us to first assess the TPS need vs. TPS capability and determine the applicability of existing TPS. Once an applicable suite of TPS is determined, the TPS thickness and mass are computed. We show that the TPS mass fraction can be as low as 5% to as high as 20%, depending on total trip time reduction and other design parameters for a range of TPS. This is a large range for TPS mass fraction. We show PICA and HEEET can indeed enable aerocapture missions, but the missions incur a mass penalty. TPS mass savings, can be further reduced with the use of conformal PICA. Advancing the development of Conformal PICA to make it robust across the entire aerothermal environment (peak heat-flux, pressure and shear) range will result in TPS mass fractions of < 10% for Ice Giant aerocapture missions such as the Neptune-Triton mission. Aerocapture allows for not only shortening the trip time but enables larger mass to be placed in orbit. Furthermore, probes deployed from orbit will benefit in reduced entry environments allowing for a lower risk TPS implementation as compared to mission designs where the probe is released prior to orbit insertion. One of the challenges for the Ice Giant community is to ensure mission designs that maximize science and allow flexibility in the placement of the entry probe. The traditional approach to release the probe ahead of the orbiter may not optimize returned science. In this presentation, we will make the case for mature TPS such as HEEET and PICA. While these materials can enable aerocapture missions, completing the development of conformal PICA and extending Conformal PICA to be more robust, will have significant impact to TPS mass efficiency and significantly enhance science return for future Gas- and Ice-Giant missions.

E Venkatapathy↗

Advanced Method to Estimate Fuel Slosh Simulation Parameters

The nutation (wobble) of a spinning spacecraft in the presence of energy dissipation is a well-known problem in dynamics and is of particular concern for space missions. The nutation of a spacecraft spinning about its minor axis typically grows exponentially and the rate of growth is characterized by the Nutation Time Constant (NTC). For launch vehicles using spin-stabilized upper stages, fuel slosh in the spacecraft propellant tanks is usually the primary source of energy dissipation. For analytical prediction of the NTC this fuel slosh is commonly modeled using simple mechanical analogies such as pendulums or rigid rotors coupled to the spacecraft. Identifying model parameter values which adequately represent the sloshing dynamics is the most important step in obtaining an accurate NTC estimate. Analytic determination of the slosh model parameters has met with mixed success and is made even more difficult by the introduction of propellant management devices and elastomeric diaphragms. By subjecting full-sized fuel tanks with actual flight fuel loads to motion similar to that experienced in flight and measuring the forces experienced by the tanks these parameters can be determined experimentally. Currently, the identification of the model parameters is a laborious trial-and-error process in which the equations of motion for the mechanical analog are hand-derived, evaluated, and their results are compared with the experimental results. The proposed research is an effort to automate the process of identifying the parameters of the slosh model using a MATLAB/SimMechanics-based computer simulation of the experimental setup. Different parameter estimation and optimization approaches are evaluated and compared in order to arrive at a reliable and effective parameter identification process. To evaluate each parameter identification approach, a simple one-degree-of-freedom pendulum experiment is constructed and motion is induced using an electric motor. By applying the estimation approach to a simple, accurately modeled system, its effectiveness and accuracy can be evaluated. The same experimental setup can then be used with fluid-filled tanks to further evaluate the effectiveness of the process. Ultimately, the proven process can be applied to the full-sized spinning experimental setup to quickly and accurately determine the slosh model parameters for a particular spacecraft mission. Automating the parameter identification process will save time, allow more changes to be made to proposed designs, and lower the cost in the initial design stages.

Schlee, Keith↗

Machine Learning based Aircraft Performance Model Estimation for Trajectory Prediction

The accurate prediction of aircraft trajectory by ground-based decision support tools is a critical component of air traffic management in the US National Airspace System (NAS). Accurate predictions of where the aircraft will be in the future or when they will arrive at specific locations (e.g., fixes) is a key enabler for sequencing and efficient arrival management of flights. Traditional physics based aircraft trajectory prediction relies on a simplified point-mass total energy model whose parameters are referred to as Aircraft Performance Model (APM) parameters. Even though the performance coefficients and weight of an aircraft are a vital part of the aircraft performance model’s predictions and accuracy, these coefficients are proprietary in nature and therefore, unavailable to decision-support tools. Current approaches freeze some coefficients to default base of aircraft data (BADA) values and optimize others. However, the APM parameters are highly coupled by the flight dynamics and prioritizing one parameter over others leads to bias and skewed predictions. To alleviate this problem, we provide a combined optimization framework to predict all the critical (thrust, drag and weight) APM parameters. This paper is focused on training Machine Learning (ML) models that map historical flights to optimized APM parameters that provide the best fit (in terms of prediction error). Our dataset obtained from NASA’s Sherlock data warehouse is comprised of thousands of historical flights and includes weather and track data collected from 2019. Using different subsets of relevant features (e.g., aircraft type), we trained several ML models to estimate the aircraft’s take off weight, drag polar coefficients (both parasitic and lift induced), and thrust settings (multiplier applied to the maximum engine thrust). The chosen flights are from three of the most common aircraft types (B738, B737, and A320) arriving at four airports (LAX, DEN, MSP, and DFW). Our ML approach is comprised of two different solutions: 1- using a subset of features that are known prior to the flight departure and do not change during flight (such as engine type, current temperature at departure & destination airports, aircraft type) and 2 - using a subset of temporal features of the flight trajectory (such as cruise altitude, Mach, airspeed, and rate of climb) in addition to the pre-departure features from the first solution. The labels or target variables are the APM parameters that were obtained by an optimized ordinary differential equations (ODE) fitting process (applied to individual flights). The ODE-fitting is very time intensive and is therefore performed offline. Thus, training an ML model to learn the relationship between the flight features and ODE-generated labels enables faster estimation of the APM parameters and is therefore amenable to real-time prediction. Various ML models including linear regression, random forest, XGBoost, and neural network were trained, and the results are compared. After model validation and hyperparameter-tuning, we observed that the Random Forest model outperformed the other three models by the overall mean square error (MSE) of 2% for the first solution and 1.5% for the second solution. Finally, the ML-derived parameters are compared against default BADA APM parameters using NASA’s Autonomy Development toolkit (ADK) simulation software. The simulation results for one of each aircraft type is shown and discussed.

Aida Sharif Rohani↗

Performance-based earthquake early warning for tall buildings

The ShakeAlert Earthquake Early Warning (EEW) system aims to issue an advance warning to residents on the West Coast of the United States seconds before the ground shaking arrives, if the expected ground shaking exceeds a certain threshold. However, residents in tall buildings may experience much greater motion due to the dynamic response of the buildings. Therefore, there is an ongoing effort to extend ShakeAlert to include the contribution of building response to provide a more accurate estimation of the expected shaking intensity for tall buildings. Currently, the supposedly ideal solution of analyzing detailed finite element models of buildings under predicted ground-motion time histories is not theoretically or practically feasible. The authors have recently investigated existing simple methods to estimate peak floor acceleration (PFA) and determined these simple formulas are not practically suitable. Instead, this article explores another approach by extending the Pacific Earthquake Engineering Research Center (PEER) performance-based earthquake engineering (PBEE) to EEW, considering that every component involved in building response prediction is uncertain in the EEW scenario. Additionally, while this idea is not new and has been proposed by other researchers, it has two shortcomings: (1) the simple beam model used for response prediction is prone to modeling uncertainty, which has not been quantified, and (2) the ground motions used for probabilistic demand models are not suitable for EEW applications. In this article, we address these two issues by incorporating modeling errors into the parameters of the beam model and using a new set of ground motions, respectively. We demonstrate how this approach could practically work using data from a 52-story building in downtown Los Angeles. Using the criteria and thresholds employed by previous researchers, we show that if peak ground acceleration (PGA) is accurately estimated, this approach can predict the expected level of human comfort in tall buildings.

58 GEOSCIENCES↗

Generating traffic-based building occupancy schedules in Chattanooga, Tennessee from a grid of traffic sensors

Building occupancy significantly impacts energy use, timing for demand impacts, and is a significant source of uncertainty in building energy models. There are relatively few sources that define building occupancy schedules and number of occupants per building or space type. More importantly, these sources define traditional schedules that are likely not to reflect the true occupancy of a given building. We construct traffic-based occupancy schedules which are more responsive to changes in mobility patterns, and which can realistically estimate occupant arrivals, departures, and counts in individual buildings.

Berres, Andy↗

Interaction of the terrestrial and atmospheric hydrological cycles in the context of the North American southwest summer monsoon

Work under this grant has used information on precipitation and water vapor fluxes in the area of the Mexican Monsoon to analyze the regional precipitation climatology, to understand the nature of water vapor transport during the monsoon using model and observational data, and to analyze the ability of the TRMM remote sensing algorithm to characterize precipitation. An algorithm for estimating daily surface rain volumes from hourly GOES infrared images was developed and compared to radar data. Estimates were usually within a factor of two, but different linear relations between satellite reflectances and rainfall rate were obtained for each day, storm type and storm development stage. This result suggests that using TRMM sensors to calibrate other satellite IR will need to be a complex process taking into account all three of the above factors. Another study, this one of the space-time variability of the Mexican Monsoon, indicate that TRMM will have a difficult time, over the course of its expected three year lifetime, identifying the diurnal cycle of precipitation over monsoon region. Even when considering monthly rainfalls, projected satellite estimates of August rainfall show a root mean square error of 38 percent. A related examination of spatial variability of mean monthly rainfall using a novel method for removing the effects of elevation from gridded gauge data, show wide variation from a satellite-based rainfall estimates for the same time and space resolution. One issue addressed by our research, relating to the basic character of the monsoon circulation, is the determination of the source region for moisture. The monthly maps produced from our study of monsoon variability show the presence of two rainfall maxima in the analysis normalized to sea level, one in south-central Arizona associated with the Mexican monsoon maximum and one in southeastern New Mexico associated with the Gulf of Mexico. From the point of view of vertically-integrated fluxes and flux divergence of water vapor from ECMWF data, most moisture at upper levels arrives from the Gulf of Mexico, while low level moisture comes from the northern Gulf of California. Composites of ECMWF analyses for wet and dry periods (classified by rain gauge data) show that both regimes show low level moisture arriving from northern and central Gulf of California. Above 700 MB, moisture comes from both source regions and the Sierra Madre Occidental. During wet periods a longer fetch through the moist air mass above western Mexico results in a greater moisture flux into the Sonoran Desert region, while there is less moisture from the Gulf of Mexico both above and below 700 mb. Work on the grant subcontract at the University of Colorado concentrated on the development of a technique useful to TRMM combining visible, infrared and passive microwave data for measuring precipitation. Two established techniques using either visible or infrared data applied over the US Southwest correlated with gauges at the 0.58 to 0.70 level. The application of some established passive microwave techniques were less successful for a variety of reason, including problems in both the gauge and satellite data quality, sampling problems and weaknesses inherent in the algorithms themselves. A more promising solution for accurate rainfall estimation was explored using visible and infrared data to perform a cloud classification, which when combined with information about the background (e.g. Iand/ocean), was used to select the most appropriate microwave algorithm from a suite of possibilities.

Dickinson, Robert E.↗

Leonid Storm Flux Analysis From One Leonid MAC Video AL50R

A detailed meteor flux analysis is presented of a seventeen-minute portion of one videotape, collected on November 18, 1999, during the Leonid Multi-instrument Aircraft Campaign. The data was recorded around the peak of the Leonid meteor storm using an intensified CCD camera pointed towards the low southern horizon. Positions of meteors on the sky were measured. These measured meteor distributions were compared to a Monte Carlo simulation, which is a new approach to parameter estimation for mass ratio and flux. Comparison of simulated flux versus observed flux levels, seen between 1:50:00 and 2:06:41 UT, indicate a magnitude population index of r = 1.8 +/- 0.1 and mass ratio of s = 1.64 +/- 0.06. The average spatial density of the material contributing to the Leonid storm peak is measured at 0.82 +/- 0.19 particles per square kilometer per hour for particles of at least absolute visual magnitude +6.5. Clustering analysis of the arrival times of Leonids impacting the earth's atmosphere over the total observing interval shows no enhancement or clumping down to time scales of the video frame rate. This indicates a uniformly random temporal distribution of particles in the stream encountered during the 1999 epoch. Based on the observed distribution of meteors on the sky and the model distribution, recommendations am made for the optimal pointing directions for video camera meteor counts during future ground and airborne missions.

Gural, Peter S.↗

Assessing Tactical Scheduler Options for Time-Based Surface Metering

NASA is committed to demonstrating a concept of integrated arrival, departure, and surface operations by 2020 under the Airspace Technology Demonstration 2 (ATD2) sub-project. This will be accomplished starting with a demonstration of flight specific time-based departure metering at Charlotte Douglass International Airport (CLT). ATD2 tactical metering capability is based on NASAs Spot And Runway Departure Advisor (SARDA) which has been tested successfully in human-in-the-loop simulations of CLT. SARDA makes use of surface surveillance data and surface modeling to estimate the earliest takeoff time for each flight active on the airport surface or ready for pushback from the gate. The system then schedules each flight to its assigned runway in order of earliest takeoff time and assigns a target pushback time, displayed to ramp controllers as an advisory gate hold time. The objective of this method of departure metering is to move as much delay as possible to the gate to minimize surface congestion and engine on-time, while keeping sufficient pressure on the runway to maintain throughput. This flight specific approached enables greater flight efficiency and predictability, facilitating trajectory-based operations and surface-airspace integration, which ATD2 aims to achieve.Throughout ATD2 project formulation and system development, researchers have continuously engaged with stakeholders and future users, uncovering key system requirements for tactical metering that SARDA did not address. The SARDA scheduler is updated every 10 seconds using real-time surface surveillance data to ensure the most up-to-date information is used to predict runway usage. However, rapid updates also open the potential for fluctuating advisories, which Ramp controllers at a busy airport like CLT find unacceptable. Therefore, ATD2 tactical metering requires that all advisories freeze once flights are ready so that Ramp controllers may communicate a single hold time when responding to pilot ready calls.

Zelinski, Shannon↗

Ground Winds Experienced by the Space Launch System Rocket on the Pad before the Artemis I Launch

Over the course of the development of the Space Launch System (SLS) human-rated heavy-lift launch vehicle, the magnitude and nature of the ground winds experienced by the rocket and its Mobile Launcher (ML) on Pad 39B at the NASA Kennedy Space Center (KSC) became a more critical environment that required characterization as well as a more accurate prediction of the vehicle and ML response in the form of detailed wind loads. The numerous reasons for the sensitivity of the launch system to these ground winds and the growing importance of high fidelity rollout and launch pad wind loading estimates are discussed in this article. A description of the wind measurement instrumentation at and around the Launch Complex is provided. A methodology is developed to estimate from these raw anemometer measurements the winds experienced by the rocket and mobile launcher on the launch pad, either in real time or during post-processing. An analysis is then performed and documented on the 121 days worth of wind measurements recorded while the SLS vehicle was secured on the pad during various launch attempts and wet dress rehearsals. This included the occurrence of a tropical storm that evolved into a named hurricane by the time it arrived on Cape Canaveral and hit the vehicle while sitting on the launch pad. Plans for further developments to improve on this predictive capability in preparation for Artemis II are also presented.

Jeremy T Pinier↗

Ground Winds Experienced by the Space Launch System Rocket on the Pad before the Artemis I Launch

Over the course of the development of the Space Launch System (SLS) human-rated heavy-lift launch vehicle, the magnitude and nature of the ground winds experienced by the rocket and its Mobile Launcher (ML) on Pad 39B at the NASA Kennedy Space Center (KSC) became a more critical environment that required characterization as well as a more accurate prediction of the vehicle and ML response in the form of detailed wind loads. The numerous reasons for the sensitivity of the launch system to these ground winds and the growing importance of high fidelity rollout and launch pad wind loading estimates are discussed in this article. A description of the wind measurement instrumentation at and around the Launch Complex is provided. A methodology is developed to estimate from these raw anemometer measurements the winds experienced by the rocket and mobile launcher on the launch pad, either in real time or during post-processing. An analysis is then performed and documented on the 121 days worth of wind measurements recorded while the SLS vehicle was secured on the pad during various launch attempts and wet dress rehearsals. This included the occurrence of a tropical storm that evolved into a named hurricane by the time it arrived on Cape Canaveral and hit the vehicle while sitting on the launch pad. Plans for further developments to improve on this predictive capability in preparation for Artemis II are also presented.

Jeremy T. Pinier↗

A single-photon lidar observes atmospheric clouds at decimeter scales: resolving droplet activation within cloud base

Abstract Clouds, crucial for understanding climate, begin with droplet formation from aerosols, but observations of this fleeting activation step are lacking in the atmosphere. Here we use a time-gated time-correlated single-photon counting lidar to observe cloud base structures at decimeter scales. Results show that the air–cloud interface is not a perfect boundary but rather a transition zone where the transformation of aerosol particles into cloud droplets occurs. The observed distributions of first-arriving photons within the transition zone reflect vertical development of a cloud, including droplet activation and condensational growth. Further, the highly resolved vertical profile of backscattered photons above the cloud base enables remote estimation of droplet concentration, an elusive but critical property to understanding aerosol–cloud interactions. Our results show the feasibility of remotely monitoring cloud properties at submeter scales, thus providing much-needed insights into the impacts of atmospheric pollution on clouds and aerosol-cloud interactions that influence climate.

54 ENVIRONMENTAL SCIENCES↗

PN velocity beneath Western New Mexico and Eastern Arizona

The experiment involved observing Pn arrivals on an areal array of 7 seismic stations located in the transition zone and along the Jemez lineament. Explosions in coal and copper mines in New Mexico and Arizona were used as energy sources as well as military detonations at White Sands Missile Range, New Mexico, Yuma, Arizona, and the Nevada Test Site. Very preliminary results suggest a Pn velocity of 7.94 km/s (with a fairly large uncertainty) beneath the study area. The Pn delay times, which can be converted to estimates of crustal thickness given knowledge of the velocity structure of the crust increase both to the north and east of Springerville, Arizona. As a constraint on the velocity of Pn, researchers analyzed the reversed refraction line GNOME-HARDHAT which passes through Springerville oriented NW to SE. This analysis resulted in a Pn velocity of 7.9-8.0 km/s for the transition zone. These preliminary results suggest that a normal Pn velocity might persist even though the crust thins (from north to south) by 15 km along the length of the Arizona-New Mexico border. If the upper mantle is currently hot anywhere in western New Mexico or eastern Arizona then the dimensions of the heat source (or sources) might be small compared to the intra-station distances of the seismic arrays used to estimate the velocity of Pn.

Jaksha, L. H.↗

An efficient method to estimate the probability density of seismic Green's functions

We present a computationally efficient method to approximate the probability distribution of seismic Green's functions given the uncertainty of an Earth model. The method is based on the Karhunen-Loève (KL) theorem and an approximation of the Green's function (or seismogram) covariance. Using Monte Carlo (MC) simulations as a control case, we demonstrate that our KL-based method can accurately reproduce a probability distribution of seismograms that results from an uncertain Earth model for a MC-derived seismogram covariance. We then describe a method to estimate the covariance of the seismograms resulting from those Earth models that is not based on MC simulations. We use the estimated Green's function covariance in conjunction with our KL-based method to produce a Green's function probability distribution, and compare that distribution to a Green's function probability distribution produced using a MC finite difference method. We find that the Green's function probability distribution approximated using our KL-based method generally mimics that produced using the MC simulations, especially for direct-arriving body waves. However the accuracy of the KL-based method generally decreases for later times in the simulated Green's function distribution.

58 GEOSCIENCES↗