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NASA NTRS2016

Maximum Likelihood Synchronization for Pulse Position Modulation with Inter-Symbol Guard Times

Deep space optical communications promises orders-of-magnitude growth in communication capacity, supporting high data rate applications such as video streaming and high-bandwidth science instruments. Pulse position modulation is the modulation format of choice for deep space applications, and by inserting inter-symbol guard times between the symbols, the signal carries the timing information needed by the demodulator. Accurately extracting this timing information is crucial to demodulating and decoding this signal. In this paper we propose a low complexity maximum likelihood timing estimator for pulse position modulation with inter-symbol guard times which significantly outperforms the prior art in this domain. We show that this estimator can achieve the same performance as prior estimators with an order-of-magnitude less signal flux, or multiple orders-of-magnitude less flux-accumulation time. Further we show that this estimator achieves the Cramer-Rao bound, making it asymptotically efficient. This method does not require an explicit synchronization sequence, freeing up channel resources for data transmission.

Rogalin, Ryan↗
NASA NTRS2019

The Diurnal Cycle of Precipitation and Organized Convection in a Set of Global Mesoscale Simulations with the NASA GEOS AGCM

The NASA Global Modeling and Assimilation Office (GMAO) has conducted a series of 40-day nonhydrostatic global simulations with horizontal grid spacing ranging from 200 km to 3 km, as part of the DYAMOND model intercomparison project. The Goddard Earth Observing System (GEOS) model was run with the Grell-Freitas scale-aware convection scheme, which smoothly reduces parameterized deep convection with increasing resolution. Here we evaluate the diurnal cycle and other statistics of precipitation and organized convection as a function of resolution. For validation we use the 0.1 degree IMERG precipitation and 4 km Merged IR brightness temperature datasets, focusing on four regions: the continental United States, Amazonia, the equatorial Indian ocean, and the Maritime Continent. Early results indicate good phase agreement but excessive magnitude of the continental diurnal cycle of precipitation at coarser resolutions, with improved magnitude as resolution increases and the role of parameterization is reduced. Convective cloud clusters are identified with a brightness temperature threshold, and we find realistic numbers of the largest clusters (>10^4 km sq) at all resolutions, while the number of smaller clusters increases with resolution, approaching observations when dx=3 km. The observed diurnal cycle in the cluster size distribution is also reproduced, with realistic magnitude in the highest resolution runs. Precipitation characteristics across cluster sizes are also examined. The results show the potential for global mesoscale simulations as a community science resource, and we invite collaboration to explore these runs in greater detail.

Arnold, Nathan↗
NASA NTRS2019

High-Performance Computing Optimization for Aladyn – Adaptive Neural Network Molecular Dynamics Mini-Application

This report provides a description and performance evaluation of the optimization techniques for high performance computing (HPC) implementation of the open source Computational Materials mini-application Aladyn (https://github.com/nasa/aladyn). Aladyn is a basic molecular dynamics code written in FORTRAN 2003, which is designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to efficiently reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of the more expensive quantum mechanics-based calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory (DFT) method. While achieving orders of magnitude faster computational performance than DFT, the ANN-based approach was still very computationally demanding compared to the conventional approach of using empirically fitted energy functions. After its initial development, Aladyn was evaluated and optimized by experts at the NASA Advanced Supercomputing (NAS) division to exploit modern supercomputer architectures. The code has been optimized for execution on multicore central processing units (CPUs), including Intel® Skylake microarchitecture, and on graphic accelerators, such as Nvidia® V100 graphic processing units (GPUs), using Open Multi-Processing (OpenMP) and Open Accelerators (OpenACC) programming interfaces. The optimization achieved a speedup of 4.7 times the baseline version on CPU performance and an additional 2.4 times on CPU+GPU performance. Atomistic computer simulations are a fundamental tool in materials research to model material properties form physics-based first principles. Atomic interaction, governed by Quantum Mechanics (QM) require sophisticated and highly computationally demanding mathematical models to calculate [1]. Classical methods use approximate functional forms, empirically fitted through a set of variable parameters to emulate atomic energies as direct functions of atomic coordinates [2]. While empirical potentials are computationally much simpler, allowing simulations of large-scale systems of up to a trillion (1012) atoms [3], they are substantially less accurate compared to quantum calculations and applicable only to very specific atomic configurations or predefined crystallographic phases. A recently suggested approach is to use heuristic machine learning methods [4], such as those based on Adaptive Neural Networks (ANNs) to predict atomic energies, after being trained on a sufficiently large database of QM-calculated structures [5,6]. This approach reduces significantly the computational complexity, allowing for simulations of orders of magnitude larger systems compared to QM-based methods without compromising accuracy. Still, compared to classical methods using empirical energy functions, ANN methods remain two- to three orders of magnitude more computationally demanding. Hence, the computational cost of simulations, together with the need for extensive training of ANNs, still makes the practical implementation of ANN-based methods quite challenging. The purpose of the Aladyn mini-application software [7], available as open source at https://github.com/nasa/aladyn, is to be a testbed for exploring possible optimization strategies to develop highly scalable parallel algorithms for ANN-based atomistic simulations. Aladyn is aimed at utilizing the architecture of the high-end modern highperformance computing (HPC) hardware based on multicore central processing units (CPUs) equipped with graphic processing unit (GPU) accelerators. Specifically, the goal is to optimize the performance on a single HPC compute node, before implementing scaling to multi-node parallelization using message passing interface (MPI). At the same time, the open source code of Aladyn can serve as a training model for students and professors in academia.

Yamakov, Vesselin I.↗
NASA NTRS2019

The Impact of Neglecting Ice Phase on Cloud Optical Depth Retrievals from AERONET Cloud Mode Observations

Clouds present many challenges to climate modelling. To develop and verify the parameterisations needed to allow climate models to represent cloud structure and processes, there is a need for high-quality observations of cloud optical depth from locations around the world. Retrievals of cloud optical depth are obtainable from radiances measured by Aerosol Robotic Network (AERONET) radiometers in “cloud mode” using a two-wavelength retrieval method. However, the method is unable to detect cloud phase, and hence assumes that all of the cloud in a profile is liquid. This assumption has the potential to introduce errors into long term statistics of retrieved optical depth for clouds that also contain ice. Using a set of idealized cloud profiles we find that, for optical depths above 20, the fractional error in retrieved optical depth is a linear function of the fraction of the optical depth that is due to the presence of ice cloud (“ice fraction”). Clouds that are entirely ice have positive errors with magnitudes of the order of 55% to 70 %. We derive a simple linear equation that can be used as a correction at AERONET sites where ice fraction can be independently estimated. Using this linear equation, we estimate the magnitude of the error for a set of cloud profiles from five sites of the Atmospheric Radiation Measurement programme. The dataset contains separate retrievals of ice and liquid retrievals; hence ice fraction can be estimated. The magnitude of the error at each location was related to the relative frequencies of occurrence in thick frontal cloud at the mid-latitude sites and of deep convection at the tropical sites – that is, of deep cloud containing both ice and liquid particles. The long-term mean optical depth error at the five locations spans the range 2– 4, which we show to be small enough to allow calculation of top-of-atmosphere flux to within 10% and surface flux to about 15 %.

Shonk, Jonathan K. P.↗
NASA NTRS2020

Multiple Shaker Placement for Ground Vibration Test of X-59 Aircraft Using Topology Optimization

A multiple shaker placement methodology is developed and tested using a topology optimization technique. Current multiple shaker placement methodology requires optimum accelerometer placement and optimum single-shaker placement techniques. The proposed methodology is tested using a finite element model of the X-59 Low Boom Flight Demonstrator aircraft. The effective independence and the driving point acceleration transfer function (DPATF) methods are used for the accelerometer placement study. In this study, four shakers are used to excite each mode more effectively during the ground vibration test; all the modes of interest thus are separated into four groups. Each shaker takes care of a separate group of modes. Grouping the modes of interest is performed utilizing topology optimization. The number of modes for each group therefore will be automatically decided during grouping. For each group of modes, perform the following two steps to determine optimal location of four shakers: 1) At each accelerometer location, compare the magnitude of DPATF values at natural frequencies, select the minimum value, and make a vector with these minimum values of the DPATF magnitudes for each group; and 2) Select the degrees of freedom corresponding to the maximum value of this vector. The objective function value is the maximum value of the vector with minimum value of the magnitude of the superposed acceleration transfer function. This objective function value is maximized by changing the modes for each group. Forty accelerometers are enough to have good correlation between mode shapes obtained from the reduced order model and the simulated ground vibration test.

Optimization Analysis↗
NASA NTRS2021

Unsteady Propagation and Mean Corrections in Open-Jet and Kevlar® Wind Tunnels

Two types of aeroacoustic wind-tunnel test section configurations have been tested in the NASA Langley Quiet Flow Facility. The first is a more traditional open-jet configuration, where test section flow passes unbounded through the facility anechoic chamber. The second is a Kevlar® panel configuration, where a tensioned Kevlar sheet constrains the test section flow from the facility anechoic chamber. For both configurations, acoustic instrumentation is in the surrounding quiescent space. Both configurations are evaluated with a laser-based pulsed acoustic source, which provides unique capability for assessing the facility unsteady acoustic propagation characteristics. Metrics based on the wander and spread of the pulses are evaluated, and show that measurements using Kevlar walls experience dramatically reduced unsteady effects when compared to the open-jet configuration. This leads to a corresponding improvement in coherence between microphones with the Kevlar configuration, by reducing the variation in magnitude and phase differences between channels. Magnitude corrections for propagation through Kevlar as compared to open-jet propagation are calculated. Although limitations in the experimental setup make quantitative analysis difficult, qualitative analysis shows Kevlar magnitude corrections similar to those determined in previous literature. Directivity effects beyond those already present for open-jet configurations are minimal. When compared with the open-jet configuration, the background noise produced by the Kevlar is found to be its one drawback, showing significantly greater levels at high frequencies.

wind tunnel testing, hybrid acoustic tunnel, facil↗
NASA NTRS2004

Scientific Objectives, measurement needs, and challenges motivating the PARAGON Aerosol Initiative

A systematic, comprehensive aerosol research framework needs to replace the current, fragmented approach. The Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) concept (Diner et al. 2004) envisions a coordinated and systematic approach for dramatically improving our understanding of aerosol climate impacts and environmental interactions. Among its scientific motivations is the need to establish, with great confidence, the magnitude of direct anthropogenic aerosol influences on climate and the magnitude and sign of indirect aerosol–cloud effects. Modeling of the industrial era temperature record indicates that net aerosol forcing is slightly less, but opposite in sign, than forcing from anthropogenic greenhouse gases (GHGs). However, the uncertainties in aerosol direct and indirect anthropogenic forcing are of the same magnitude as the effects themselves (Penner et al. 2001; Ramaswamy et al. 2001), and are the dominant sources of uncertainty in current estimates of total anthropogenic climate forcing. A major cause of uncertainty is the tremendous tropospheric aerosol variability in space and time. On regional scales, aerosols can have a much greater effect than GHGs, especially at the earth’s surface.

Wielicki, Bruce A.↗
NASA NTRS2018

Toward a NASA Deep Space Optical Communications System

As discussed at SpaceOps in 2016, we expect the data rates from deep space missions to increase approximately one order of magnitude per decade for the next 50 years. The first order of magnitude improvement will come from existing plans for radio frequency (RF) communications including enhancements to both spacecraft and Deep Space Network (DSN) facilities. The next two orders of magnitude are predicted to come from the introduction of deep space optical communications. Studies indicate that optical receive apertures of between 8m12m are desired. The large cost of dedicated receive telescopes makes this method unrealistic – at least in the near-term. The cost of large optical ground terminals is driven primarily by the cost of the optics and by the cost of a stable structure for the telescope. We propose a novel hybrid design in which existing DSN 34m beam waveguide (BWG) radio antennas can be modified to include an 8m equivalent optical primary. By utilizing a low-cost segmented spherical mirror optical design, pioneered by the optical astronomical community, and by exploiting the already existing extremely stable large radio aperture structures in the DSN, we can minimize both of these cost drivers for implementing large optical communications ground terminals. Two collocated hybrid RF/optical antennas could be arrayed to synthesize the performance of an 11.3m receive aperture to support more capable or more distant space missions or used separately to communicate with two optical spacecraft simultaneously. NASA is in the midst of building six new 34m BWG antennas in the DSN. The final two are planned to be built at the DSN Goldstone, California and Canberra complexes. We are now investigating building these last two antennas as RF/optical hybrids. By delaying their operational dates by two years, we would be able to add the 8m optical receive capability for these two antennas while fitting within existing budgetary constraints. This paper describes the hybrid antenna design, the technical challenges being addressed, and plan for using this concept, together with ongoing work on optical flight terminals, to infuse operation optical communications into deep space missions.

Cornwell, Donald M.↗
NASA NTRS2019

The HST Lightcurve of (486958) 2014 MU69

We report Hubble Space Telescope (HST) lightcurve observations of the New Horizons spacecraft encounter Kuiper Belt object (KBO) (486958) 2014 MU69 acquired near opposition in July 2017. In order to plan the optimum flyby sequence the New Horizons mission planners needed to learn as much as possible about the target in advance of the encounter. Specifically, from lightcurve data, encounter timing could be adjusted to accommodate a highly elongated, binary, or rapidly rotating target. HST astrometric (Porter et al., 2018) and stellar occultation (Buie et al., 2018) observations constrained MU69's orbit and diameter (21–41 km for an albedo of 0.15–0.04), respectively. Photometry from the astrometric dataset suggested a variability of ≥0.3 mags, but they did not determine the period or provide shape information. To that end we strategically spaced 24 HST orbits over 9 days to investigate rotation periods from approximately 2–100 h and to better constrain the lightcurve amplitude. Until New Horizons detected MU69 in its optical navigation images beginning in August 2018, this HST lightcurve campaign provided the most accurate photometry to date. The mean variation in our data is 0.15 magnitudes which suggests that MU69 is either nearly spherical (a:b axis ratio of 1:1.15), or its pole vector is pointed near the line of sight to Earth; this interpretation does not preclude a near-contact binary or bi-lobed object. However, image stacks do conclude that MU69 does not have a binary companion ≥2000 km with a sensitivity to 29th magnitude (an object a few km in size for an albedo of 0.04–0.15). Our data are not of sufficient signal to noise to uniquely determine the period or amplitude, however, they did provide the necessary information for spacecraft planning. We report with confidence that MU69 is not both rapidly rotating and highly elongated (which we define as a lightcurve amplitude ≥ 0.5 magnitude). Since this paper is being published post fly-by, we note that our results are consistent with the fly-by imagery and orientation of MU69 (Stern et al., 2019). The combined dataset also suggests that within the KBO lightcurve literature there are likely other objects which share a geometric configuration like MU69 resulting in an underestimate of the contact binary fraction for the Cold Classical Kuiper Belt.

S D Benecchi↗
NASA NTRS2021

Uncertainties, Limits, and Benefits of Climate Change Mitigation for Soil Moisture Drought in Southwestern North America

Over the last two decades, southwestern North America (SWNA) has been in the grip of one of the most severe droughts of the last 1,200 years, with one third to nearly one half of its severity attributable to climate change. We analyze how the risk of extreme soil moisture droughts in SWNA, analogous to the most severe 21-year (≥ in magnitude to 2000–2020) and single-year (≥ in magnitude to 2002) events of the last several decades, changes in projections from Phase 6 of the Coupled Model Intercomparison Project. By the end of the 21st century, SWNA experiences robust (R ≥ 0.80) soil moisture drying and substantial increases in extreme single-year drought risk that scale strongly with warming, spanning an 8%–26% probability of occurrence across +2–4 K. Notably, our results show that 21-year droughts analogous to 2000–2020 are up to 5 times more likely than extreme single-year droughts under all levels of warming (≈50%). These high levels of 21-year drought risk are largely invariant across scenarios because of large spring precipitation declines in half the models, shifting SWNA into a drier mean state. Despite projections of this sweeping and ostensibly inevitable increase in 21-year drought risk, climate mitigation reduces their severity by reducing the magnitude of extreme single-year droughts during these events. Our results emphasize both the importance of preparing SWNA for imminent increases in persistent drought events and constraining projected precipitation uncertainty to better resolve future long-term drought risk.

drought↗
NASA NTRS2021

A High Dynamic-Range Photon-Counting Receiver for Deep Space Optical Communication

The Deep Space Optical Communication (DSOC) project will demonstrate free-space optical communication at almost 3 AU, or 3 orders of magnitude further than any previous attempt. DSOC will utilize the 5m Palomar Hale Telescope to receive the downlink signal, which will couple the downlink light onto an optical table and into a superconducting nanowire single photon detector (SNSPD). The output of the SNSPD is digitized by the Ground Laser Receiver Signal Processing Assembly (GSPA) using a high throughput streaming time to digital converter (TDC). The GSPA is a scalable FPGA-based receiver which demodulates and decodes the DSOC downlink signal through novel signal processing algorithms implemented on Xilinx UltraScale+ FPGAs, as well as Python-based software monitor and control routines. Exploiting the unique TDC-based architecture, the GSPA supports over four orders of magnitude of downlink data rates across multiple orders of magnitude of signal and background powers. In this paper we present an overview of the hardware, firmware and software architectures to implement this system, as well as performance analysis for links ranging from near-Earth to 2.8 AU.

Srinivasan, Meera↗
NASA NTRS2022

Observations of Particle Number Size Distributions and New Particle Formation in Six Indian Locations

Atmospheric new particle formation (NPF) is a crucial process driving aerosol number concentrations in the atmosphere; it can significantly impact the evolution of atmospheric aerosol and cloud processes. This study analyses at least 1 year of asynchronous particle number size distributions from six different locations in India. We also analyze the frequency of NPF and its contribution to cloud condensation nuclei (CCN) concentrations. We found that the NPF frequency has a considerable seasonal variability. At the measurement sites analyzed in this study, NPF frequently occurs in March–May (pre-monsoon, about 21 % of the days) and is the least common in October–November (post-monsoon, about 7 % of the days). Considering the NPF events in all locations, the particle formation rate (J_(SDS)) varied by more than 2 orders of magnitude (0.001–0.6 /cu.cm s) and the growth rate between the smallest detectable size and 25 nm (GR_(SDS-25 nm)) by about 3 orders of magnitude (0.2–17.2 nm/h). We found that JSDS was higher by nearly 1 order of magnitude during NPF events in urban areas than mountain sites. GRSDS did not show a systematic difference. Our results showed that NPF events could significantly modulate the shape of particle number size distributions and CCN concentrations in India. The contribution of a given NPF event to CCN concentrations was the highest in urban locations (4.3 × 10^(3) /cu.cm per event and 1.2 × 10^(3)/cu.cm per event for 50 and 100 nm, respectively) as compared to mountain background sites (2.7 × 10^(3)/cu.cm per event and 1.0 × 10^(3)/cu.cm per event, respectively). We emphasize that the physical and chemical pathways responsible for NPF and factors that control its contribution to CCN production require in situ field observations using recent advances in aerosol and its precursor gaseous measurement techniques.

particle number size distributions↗
NASA NTRS2022

Seasonal Tidewater Glacier Terminus Oscillations Bias Multi-Decadal Projections of Ice Mass Change

Numerical, process-based simulations of tidewater glacier evolution are necessary to project future sea-level change under various climate scenarios. Previous work has shown that nonlinearities in tidewater glacier and ice stream dynamics can lead to biases in simulated ice mass change in the presence of noisy forcings. Ice sheet modeling projections that are used in the IPCC Assessment Report 6 (AR6) utilize atmospheric and oceanic forcings at annual temporal resolution, omitting any higher frequency forcings. Here, we quantify the effect of seasonal (<1 year) tidewater glacier terminus oscillations on decadal-scale (30 years) mass change. We use an idealized geometry to mimic realistic tidewater glacier geometries and investigate the impact of the magnitude of seasonal oscillations, bed slope at the glacier terminus, and basal friction law. We find that omitting seasonal terminus motion results in biased mass change projections, with up to an 39% underestimate or 25% overestimate of mass loss when seasonality is neglected, depending on bed slope and magnitude of oscillations. The bias is most sensitive to the magnitude of the seasonal terminus oscillations and exhibits very little sensitivity to choice of friction law. Although omitting seasonal terminus motion may bias mass change projections of individual glaciers, further work is needed to investigate the impact on ice sheet mass change projections. In order to achieve this, seasonality in atmospheric and oceanic forcings must be adequately represented and observations of seasonal terminus positions and tidewater glacier thickness changes must be acquired to evaluate numerical models. Note: Zip folder contains all videos listed in the supplemental document and can be downloaded for viewing.

D. Felikson↗
NASA NTRSDate not supplied

Mass-Specific Power at the Organism and Biosphere Level

The concept of mass-specific power (MSP) quantitatively relates energy flux to the biomass that flux can sustain. We sought to assess the range and distribution of MSP as expressed at both the organism and biosphere level. The former serves to establish what is possible, and what predominates, in physiological terms; the latter reflects the expression of that physiological potential in an environmental context. To assess the potential range of MSP across a diversity of organisms and physiological states, we compiled a data set of more than 10,000 individual MSP measurements, encompassing more than 2900 unique species and spanning 22 orders of magnitude in body mass. Across the data set, MSP varies over six orders of magnitude, from 3 x 10-5 to 49 Watts per gram biomass carbon (W/gC), but the majority of measured values fall within a relatively narrow range of 0.018 ± 6.4-fold W/gC. It is well documented, and clearly expressed in the data set, that MSP exhibits a strong mass dependence within specific taxa (e.g., birds, mammals, and many others); however, MSP exhibits no mass dependence when considering the data set overall. To assess the expression of MSP in environmental context, we estimated energy utilization rates within eight distinct components of the global biosphere, and for the biosphere overall, and used recently published estimates of biomass within those components to compute MSP. We estimate MSP of 0.005 W/gC for the global biosphere as a whole. The close agreement with the organism-level all-species mean (within 4-fold) is noteworthy because the organism-level data set is dominated in statistical terms by animals, while the global biosphere is dominated in mass terms by trees and microorganisms. The various components of the microbe-dominated marine biosphere exhibit a systematic 5 order of magnitude decrease in MSP from the top of the water column (marine primary producers: 0.9 W/gC) to the depths of the sediment column (> 1m sediment biota: 3 x 10-6 W/gC). Biomass turnover rates, combined with the microbial capacity for both high specific growth rates and low maintenance rates, appear to underlie this large range in MSP, which is not expressed to the same extent in the terrestrial biosphere.

Tori M Hoehler↗
NASA NTRSDate not supplied

Impacts of Improved Process Representation of Particle Dry Deposition on PM Pollution in a Global Chemistry-Climate Model: Differences Across Regions, Seasons, and PM Sizes

Dry deposition (DD) is a primary removal pathway of particulate matter (PM). The aerosol DD schemes in most global models do not reflect current mechanistic understanding gleaned from observations. The NASA GISS global chemistry-climate model has a new and more dynamic DD scheme that largely captures observed changes in deposition velocities with particle size. We quantify the response of simulated PM to changes in the DD scheme for the Northeast US, Central Europe, North China Plain, and Punjab. Relative to the widely used old scheme, the new scheme shows higher annual PM2.5 for all regions (up to +14%) except C. Europe where there are very small decreases. For PM1, annual increases occur over all regions (up to +20%). For PM10, there are decreases in C. Europe (-8%) and very small decreases in the NE US yet increases (up to +12%) in Punjab and N. China Plain. While there are always increases across seasons for Punjab and N. China Plain, there are both seasonal increases and decreases for the NE US and C. Europe. Given incomplete understanding of observed variations in deposition velocities for a given particle size, we perform sensitivity simulations that perturb the magnitude of the deposition velocities simulated by the new scheme. The annual PM response to increasing DD is similar in magnitude to decreasing DD, implying linearity in the PM sensitivity to DD. The relative annual response to perturbing the DD magnitude is weaker over Punjab and sometimes N. China Plain than the NE US and C. Europe. Higher PM over Punjab and N. China Plain implies a stronger sensitivity to DD when aerosol abundances are low. More mechanistic representation of aerosol DD can sometimes improve or worsen existing model PM biases, which suggests that PM biases due to other processes can be confounded or compounded by biases in DD. Further improvements to DD parameterizations require not only more observational constraints on aerosol deposition velocities but also an advanced understanding of the processes controlling observed variability.

Environmental pollution↗
NASA NTRSDate not supplied

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↗
NASA NTRS2022

Using Desis and EO-1 Hyperion Reflectance Time Series for the Assessment of Vegetation Traits and Gross Primary Production (GPP)

This study evaluates the potential of the DLR Earth Sensing Imaging Spectrometer (DESIS) visible through near-infrared (VNIR) surface reflectance to augment the EO-1 Hyperion full spectrum (400-2400 nm) reflectance collection over vegetated flux sites to extend the reflectance time series up to the present. We compared DESIS and Hyperion surface reflectance magnitude and variability at a pseudo-invariant site (PICS) and a vegetated flux site (VFS). VNIR reflectance magnitudes between the two sensors did not significantly differ at the PICS. However, DESIS variability was higher, likely due to differences in the data acquisition time and observation geometry. Using empirical and biophysical models, both DESIS and Hyperion datasets captured the seasonal variations in gross primary production (GPP) and canopy bio-physical parameters such as chlorophyll content, leaf area index (LAI), and senescent material at the VFS. Differences in the magnitudes of the bio-physical parameters were observed, likely due to the differences in the sensors spectral range and resolution. Using VNIR reflectance from EO-1 Hyperion with DESIS convolved to Hyperion spectral resolution to estimate canopy chlorophyll and GPP, we demonstrate that combining historic and current space-based reflectance data in a common multi-sensor approach is feasible. This is of importance for extending the reflectance record established with EO-1 Hyperion to provide continuity with the current orbital instruments (e.g., DESIS/ISS, PRISMA/ASI) and the forthcoming NASA Surface Biology and Geology (SBG), ESA CHIME and DLR EnMAP satellite missions, which is of key importance for comparisons of current and past trends in the seasonal dynamics of vegetation traits and photosynthetic function.

DESIS↗
NASA NTRS2024

Improved Chemistry and Attenuation Models for Communication Blackout Simulation During Mars 2020 Entry

As a blunt body enters a planetary atmosphere, a plasma forms in the hypersonic shock layer and attenuates radio communication causing signal blackout for some duration of the entry sequence. In our previous work,1 computational fluid dynamics (CFD) was applied to model the entry flow around the Mars 2020 spacecraft, including ionization and electron density throughout the flow field, and predict ultra-high frequency (UHF) radio wave attenuation due to electrons. In total, 17 chemical species and their spatial profiles are modelled around the Mars 2020 spacecraft at 11 different points in time during entry. Although the simulation predicted the onset of attenuation well, the timing of the end of the predicted blackout window significantly preceded the end time observed during the 2021 landing. The present work seeks to improve the attenuation model by accounting for the fact that electrons undergo collisions with heavier species in the flow, which is an effect that was neglected in previous analyses. It is determined that including electron collisions increases the overall magnitude of attenuation predicted especially towards the end of the measured attenuation period, improving qualitative agreement between predicted and measured attenuation to both spacecraft receiving the signal from Mars 2020. To explore the remaining uncertainty in signal attenuation predictions further, a sensitivity study is performed to investigate the impact of associative ionization and electron-impact ionization rate coefficients on the electron density predicted by CFD and on the resulting attenuation predictions. These coefficients are believed to contain up to order-of-magnitude uncertainty, and therefore may significantly affect the number density of electrons throughout the flow field. Variations in associative ionization coefficients demonstrate significant impact on the magnitude of attenuation due to variation in the electron density coming from associative ionization. However, the start and end times of the predicted signal attenuation period are only slightly impacted by said variation.

Eve Papajak↗