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NASA NTRS2008

Spacecraft Maximum Allowable Concentrations for Airborne Contaminants

The enclosed table lists official spacecraft maximum allowable concentrations (SMACs), which are guideline values set by the NASA/JSC Toxicology Group in cooperation with the National Research Council Committee on Toxicology (NRCCOT). These values should not be used for situations other than human space flight without careful consideration of the criteria used to set each value. The SMACs take into account a number of unique factors such as the effect of space-flight stress on human physiology, the uniform good health of the astronauts, and the absence of pregnant or very young individuals. Documentation of the values is given in a 5 volume series of books entitled "Spacecraft Maximum Allowable Concentrations for Selected Airborne Contaminants" published by the National Academy Press, Washington, D.C.

John T James↗
NASA NTRS2009

The Maximum Free Magnetic Energy Allowed in a Solar Active Region

Two whole-active-region magnetic quantities that can be measured from a line-of-sight magnetogram are (sup L) WL(sub SG), a gauge of the total free energy in an active region's magnetic field, and sup L(sub theta), a measure of the active region's total magnetic flux. From these two quantities measured from 1865 SOHO/MDI magnetograms that tracked 44 sunspot active regions across the 0.5 R(sub Sun) central disk, together with each active region's observed production of CMEs, X flares, and M flares, Falconer et al (2009, ApJ, submitted) found that (1) active regions have a maximum attainable free magnetic energy that increases with the magnetic size (sup L) (sub theta) of the active region, (2) in (Log (sup L)WL(sub SG), Log(sup L) theta) space, CME/flare-productive active regions are concentrated in a straight-line main sequence along which the free magnetic energy is near its upper limit, and (3) X and M flares are restricted to large active regions. Here, from (a) these results, (b) the observation that even the greatest X flares produce at most only subtle changes in active region magnetograms, and (c) measurements from MSFC vector magnetograms and from MDI line-of-sight magnetograms showing that practically all sunspot active regions have nearly the same area-averaged magnetic field strength: =- theta/A approximately equal to 300 G, where theta is the active region's total photospheric flux of field stronger than 100 G and A is the area of that flux, we infer that (1) the maximum allowed ratio of an active region's free magnetic energy to its potential-field energy is ~1, and (2) any one CME/flare eruption releases no more than a small fraction (less than ~10%) of the active region's free magnetic energy. This work was funded by NASA's Heliophysics Division and NSF's Division of Atmospheric Sciences.

Moore, Ronald L.↗
NASA NTRS2012

Contribution of National near Real Time MODIS Forest Maximum Percentage NDVI Change Products to the U.S. ForWarn System

This presentation reviews the development, integration, and testing of Near Real Time (NRT) MODIS forest % maximum NDVI change products resident to the USDA Forest Service (USFS) ForWarn System. ForWarn is an Early Warning System (EWS) tool for detection and tracking of regionally evident forest change, which includes the U.S. Forest Change Assessment Viewer (FCAV) (a publically available on-line geospatial data viewer for visualizing and assessing the context of this apparent forest change). NASA Stennis Space Center (SSC) is working collaboratively with the USFS, ORNL, and USGS to contribute MODIS forest change products to ForWarn. These change products compare current NDVI derived from expedited eMODIS data, to historical NDVI products derived from MODIS MOD13 data. A new suite of forest change products are computed every 8 days and posted to the ForWarn system; this includes three different forest change products computed using three different historical baselines: 1) previous year; 2) previous three years; and 3) all previous years in the MODIS record going back to 2000. The change product inputs are maximum value NDVI that are composited across a 24 day interval and refreshed every 8 days so that resulting images for the conterminous U.S. are predominantly cloud-free yet still retain temporally relevant fresh information on changes in forest canopy greenness. These forest change products are computed at the native nominal resolution of the input reflectance bands at 231.66 meters, which equates to approx 5.4 hectares or 13.3 acres per pixel. The Time Series Product Tool, a MATLAB-based software package developed at NASA SSC, is used to temporally process, fuse, reduce noise, interpolate data voids, and re-aggregate the historical NDVI into 24 day composites, and then custom MATLAB scripts are used to temporally process the eMODIS NDVIs so that they are in synch with the historical NDVI products. Prior to posting, an in-house snow mask classification product is computed for the current compositing period and integrated into the change images to account for snow related NDVI drops. The supplemental snow classification product was needed because other available QA cloud/snow mask typically underestimates snow cover. MODIS true and false color composites were also computed from eMODIS reflectance data and the true color RGBs are also posted on ForWarn?s FCAV; this data is used for assessing apparent occasional quality issues on the change products due to residual unmasked cloud cover. New forest change products are posted with typical latencies of 1-2 days after the last input eMODIS data collection date for a given 24 day compositing period.

Spruce, Joseph P.↗
NASA NTRS1944

Effect of Mach and Reynolds Numbers on the Power-Off Maximum Lift Coefficient Obtainable on a P-39N-1 Airplane as Determined in Flight

Flight tests were conducted on a Bell P-39N-1 airplane to determine the variation with Mach and Reynolds numbers of the maximum lift coefficient obtainable. The tests were made with the propeller in the constant-speed high-pitch setting and with the power off in order to minimize the effect of power and the propeller. The investigation covered a Mach number range of 0.146 to 0.655 and a Reynolds-number range of 4,900,000 to 17,100,000.The results of the investigation indicated that the maximum lift coefficient obtainable decreased markedly with an increase in Mach number for a given Reynolds number and exhibited a tendency to increase with an increase in Reynolds number for a given Mach number up to a Mach number of 0.55.

James M Nissen↗
NASA NTRS2015

Simplified Methodology to Estimate the Maximum Liquid Helium (LHe) Cryostat Pressure from a Vacuum Jacket Failure

The aircraft-based Stratospheric Observatory for Infrared Astronomy (SOFIA) is a platform for multiple infrared astronomical observation experiments. These experiments carry sensors cooled to liquid helium temperatures. The liquid helium supply is contained in large (i.e., 10 liters or more) vacuum-insulated dewars. Should the dewar vacuum insulation fail, the inrushing air will condense and freeze on the dewar wall, resulting in a large heat flux on the dewar's contents. The heat flux results in a rise in pressure and the actuation of the dewar pressure relief system. A previous NASA Engineering and Safety Center (NESC) assessment provided recommendations for the wall heat flux that would be expected from a loss of vacuum and detailed an appropriate method to use in calculating the maximum pressure that would occur in a loss of vacuum event. This method involved building a detailed supercritical helium compressible flow thermal/fluid model of the vent stack and exercising the model over the appropriate range of parameters. The experimenters designing science instruments for SOFIA are not experts in compressible supercritical flows and do not generally have access to the thermal/fluid modeling packages that are required to build detailed models of the vent stacks. Therefore, the SOFIA Program engaged the NESC to develop a simplified methodology to estimate the maximum pressure in a liquid helium dewar after the loss of vacuum insulation. The method would allow the university-based science instrument development teams to conservatively determine the cryostat's vent neck sizing during preliminary design of new SOFIA Science Instruments. This report details the development of the simplified method, the method itself, and the limits of its applicability. The simplified methodology provides an estimate of the dewar pressure after a loss of vacuum insulation that can be used for the initial design of the liquid helium dewar vent stacks. However, since it is not an exact tool, final verification of the dewar pressure vessel design requires a complete, detailed real fluid compressible flow model of the vent stack. The wall heat flux resulting from a loss of vacuum insulation increases the dewar pressure, which actuates the pressure relief mechanism and results in high-speed flow through the dewar vent stack. At high pressures, the flow can be choked at the vent stack inlet, at the exit, or at an intermediate transition or restriction. During previous SOFIA analyses, it was observed that there was generally a readily identifiable section of the vent stack that would limit the flow – e.g., a small diameter entrance or an orifice. It was also found that when the supercritical helium was approximated as an ideal gas at the dewar condition, the calculated mass flow rate based on choking at the limiting entrance or transition was less than the mass flow rate calculated using the detailed real fluid model2. Using this lower mass flow rate would yield a conservative prediction of the dewar’s wall heat flux capability. The simplified method of the current work was developed by building on this observation.

Ungar, Eugene K.↗
NASA NTRS2017

The PMIP4 Contribution to CMIP6-Part 4: Scientific Objectives and Experimental Design of the PMIP4-CMIP6 Last Glacial Maximum Experiments and PMIP4 Sensitivity Experiments

The Last Glacial Maximum (LGM, 21,000 years ago) is one of the suite of paleoclimate simulations included in the current phase of the Coupled Model Intercomparison Project (CMIP6). It is an interval when insolation was similar to the present, but global ice volume was at a maximum, eustatic sea level was at or close to a minimum, greenhouse gas concentrations were lower, atmospheric aerosol loadings were higher than today, and vegetation and land-surface characteristics were different from today. The LGM has been a focus for the Paleoclimate Modelling Intercomparison Project (PMIP) since its inception, and thus many of the problems that might be associated with simulating such a radically different climate are well documented. The LGM state provides an ideal case study for evaluating climate model performance because the changes in forcing and temperature between the LGM and pre-industrial are of the same order of magnitude as those projected for the end of the 21st century. Thus, the CMIP6 LGM experiment could provide additional information that can be used to constrain estimates of climate sensitivity. The design of the Tier 1 LGM experiment (lgm) includes an assessment of uncertainties in boundary conditions, in particular through the use of different reconstructions of the ice sheets and of the change in dust forcing. Additional (Tier 2) sensitivity experiments have been designed to quantify feedbacks associated with land-surface changes and aerosol loadings, and to isolate the role of individual forcings. Model analysis and evaluation will capitalize on the relative abundance of paleoenvironmental observations and quantitative climate reconstructions already available for the LGM.

Kageyama, Masa↗
NASA NTRS2018

Maximum Sample Temperature for Mars Sample Return: A Historical Perspective

Since the first Mars Sample Return (MSR) report published by the Jet Propulsion Laboratory (JPL) in 1974 [1], a series of panels, reports, and white papers have recognized the importance of sample temperature and offered an informed sample maximum temperature (henceforth SMT) limit for returning martian samples to Earth. The Mars Sample Handling and Requirements Panel (MSHARP, 1999) stated that "[t]he main issue in sample preservation is temperature" [2]. More recently, the Mars Exploration Program Analysis Group (MEPAG)'s "Science Priorities for Mars Sample Return" report (2008), declared that "[s]ignificant loss, particularly to biological studies, occurs if samples reach +50C for three hours", whereby "scientific objectives related to life goals could be seriously compromised" [3]. By contrast, the Mars 2020 mission has adopted a SMT of +60C as spelled out in Beaty et al., 2016 [4]. Samples will be collected and then deposited on the surface in sealed tubes for possible retrieval and return to Earth. Beaty et al. [4] calculates that the samples will experience maximum temperatures of ~+30 to +60C, depending on latitude. At present, there is no mission requirement for the measurement/data logging of sample temperature during this period. We will explore the history of martian SMTs, as they have been recorded since 1974 [1], effectively representing input across multiple generations of Mars scientists. Ten separate publications present SMTs for MSR samples [1-10]. One report [10] is for a mission concept specifically designed to exclude life detection investigations, and recommended an SMT of 50C. Another did not specify a temperature, recommending "Mars ambient temperature" [5]. Of the remaining eight, SMTs are given as: -30C [1], -20C [3], 60C [4], -73 to 41C depending on sample type [6], -40C [7], -43 to 13C depending on type [2,8], and -33C [9]. If we restrict the temperatures to samples highlighted in the Mars 2020 mission goals, i.e. organics-bearing and sedimentary rocks, then the average SMT is -28+/-39C (n=8). Applying a Dixon's Q Test at P=0.05 (two-tailed), the 60C SMT [4] fails with Q=0.602 versus Qcrit=0.526. Excluding the outlier produces an average SMT of -40+/-17C (n=7). Therefore, the average SMT expressed by the Mars science community over the past 44 years (two generations) is a sample temperature no greater than -40C. The difference in chemical reaction rates between this average SMT and Beaty et al [4] can be estimated using the Arrhenius equation. Assuming a generic chemical reaction with an activation energy of 50 kJ/mol and a pre-exponential factor invariant with temperature, this reaction will proceed 2300x faster at 60C than at -40C. To illustrate the effects of the increased reaction rate, consider 10 ppb of alanine in a Mars 2020 cache, and assume that it becomes unmeasurable if it degrades to 1 ppb, as per the Mars 2020 Organic Contamination Panel contamination limits [11]. If we illustrate the effect with an arbitrary degradation rate such that the alanine will become undetectable in ten years at -40C, then the same 10 ppb alanine degrades beyond detectability in only 38 days at 60C. Further research is required to quantify expected analyte losses in the cached samples due to thermal processing.

Fries, Marc↗
NASA NTRS2019

The Implementation of Maximum Likelihood Estimation in Space Launch System Vehicle Design

The Space Launch System uses a Maximum Likelihood Estimation process in conjunction with Design of Experiments to develop statistically representative vehicles for the Block 1 configuration. These vehicles are then used to estimate maximum load conditions for simulating stressing cases in other simulations. This paper discusses the modeling process and how SLS captures manufacturing uncertainty in the launch vehicle design. It also provides an overview of the differences between Block 1 statistical representations. This paper also discusses proper grid choice as well as which uncertainties drive the vehicle design.

Stein, W. B.↗
NASA NTRS2019

On the Maximum Pair Multiplicity of Pulsar Cascades

We study electron–positron pair production in polar caps of energetic pulsars to determine the maximum multiplicity of pair plasma a pulsar can produce under the most favorable conditions. This paper complements and updates our study of pair cascades presented in Timokhin & Harding (2015) with a more accurate treatment of the effects of ultrastrong B approximately greater than 3 x 10 (exp 12) G magnetic fields and emission processes of primary and secondary particles. We include pairs produced by curvature and synchrotron radiation photons as well as resonant Compton-scattered photons. We develop a semianalytical model of electron–positron cascades that can efficiently simulate pair cascades with an arbitrary number of microphysical processes and use it to explore cascade properties for a wide range of pulsar parameters. We argue that the maximum cascade multiplicity cannot exceed approximately a few x 10 (exp 5) and that the multiplicity has a rather weak dependence on pulsar period. The highest multiplicity is achieved in pulsars with magnetic field 4 x 10 (exp 12) is approximately greater than B is approximately greater than 10 (exp 13) G and hot surfaces, with T is approximately greater than 10 (exp 6)K. We also derive analytical expressions for several physical quantities relevant for electromagnetic cascade in pulsars, which may be useful in future works on pulsar cascades, including the upper limit on cascade multiplicity and various approximations for the parameter χ, the exponential factor in the expression for photon attenuation in strong magnetic fields.

Timokhin, A. N.↗
NASA NTRS2019

Maximum Carbon Uptake Rate Dominates the Interannual Variability of Global Net Ecosystem Exchange

Terrestrial ecosystems contribute most of the interannual variability (IAV) in atmospheric carbon dioxide (CO2) concentrations, but processes driving the IAV of net ecosystem CO2 exchange (NEE) remain elusive. For a predictive understanding of the global C cycle, it is imperative to identify indicators associated with ecological processes that determine the IAV of NEE. Here, we decompose the annual NEE of global terrestrial ecosystems into their phenological and physiological components, namely maximum carbon uptake (MCU) and release (MCR), the carbon uptake period (CUP), and two parameters, α and β, that describe the ratio between actual versus hypothetical maximum C sink and source, respectively. Using long‐term observed NEE from 66 eddy covariance sites and global products derived from FLUXNET observations, we found that the IAV of NEE is determined predominately by MCU at the global scale, which explains 48% of the IAV of NEE on average while α, CUP, β, and MCR explain 14%, 25%, 2%, and 8%, respectively. These patterns differ in water‐limited ecosystems versus temperature‐ and radiation‐limited ecosystems; 31% of the IAV of NEE is determined by the IAV of CUP in water‐limited ecosystems, and 60% of the IAV of NEE is determined by the IAV of MCU in temperature‐ and radiation‐limited ecosystems. The Lund‐Potsdam‐Jena (LPJ) model and the Multi‐scale Synthesis and Terrestrial Model Inter‐comparison Project (MsTMIP) models underestimate the contribution of MCU to the IAV of NEE by about 18% on average, and overestimate the contribution of CUP by about 25%. This study provides a new perspective on the proximate causes of the IAV of NEE, which suggest that capturing the variability of MCU is critical for modeling the IAV of NEE across most of the global land surface.

Fu, Zheng↗
NASA NTRSDate not supplied

Predicting Maximum Thermal Response in a Li-ion Cell as a Thermal Runaway Predictor for a UAV Fight

As the energy storage devices continue to "pack" more energy in a small space, any damage, battery component failure, manufacturing defect, or electrically abusing the battery can lead to catastrophic thermal runaway events. A catastrophic thermal event in a cell leads to high temperature, in some instances to spewing of battery materials due to gas development from side reactions initiated due to high internal temperatures. Moreover, a thermal runaway can propagate from a single "failed" cell to a whole battery pack, resulting in a more serious event. The commercial and automotive sectors need to mitigate thermal runaway events. An electric aircraft (or air taxi) has no alternative in the event of a failure, so preventing such events is paramount. Currently, battery prognostics algorithms only predict the state-of-charge (SOC) and end-of-life (EOL) of a Li-ion battery in a UAV (unmanned air vehicle), but do not predict the maximum temperature during a flight or the likelihood of thermal runaway. Our current work focuses on adding the thermal model (based on Birkl's OCV model, in Ref. [1]) to the existing hybrid electrochemical model (single-particle model with lumped parameters as in Ref. [2]) to determine end-of-discharge, end-of-life, and maximum temperature during discharge.

Thermal runaway↗
NASA NTRSDate not supplied

Frequency Domain Quasi Maximum Likelihood Identification of Low Order Aeroservoelastic Models from Flight-Test Data

Background and Motivation - Low Order Equivalent System (LOES) - From handling qualities analysis - Traditionally simplifying complex control law and plant - More easily understood form - Extend LOES to a complex model due to aeroelasticity - Maximum likelihood (Filter Error) System Identification - Z = H_loes (U + W) + V - There are a lot of parameters - Estimate noise parameters - Extra outputs mean extra parameters to estimate - Usually assume noise model to simplify - Output Error and Equation Error - Results in biased estimates of the parameters - Sensing flexible aircraft have many outputs - Quasi maximum likelihood exploits redundancy of outputs

Jeffrey Ouellette↗
NASA NTRSDate not supplied

Nitric Oxide Concentrations from Solar Maximum to Solar Minimum Years Derived from SABER

Nitric oxide (NO) is of particular importance in the upper atmosphere nominally the region between 100 km and 250 km, as it plays the role in cooling and regulating the energy budget of the system. The NO cooling rates have been routinely derived for the past two decades from the measurements made by Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument on the Thermosphere Ionosphere Mesosphere Energetics and Dynamics satellite (TIMED) satellite since 2002. However, a comprehensive long-term dataset of global thermospheric NO concentration as a function of local time is currently unavailable. Given that solar activity significantly influences NO abundance on timescales ranging from days to decades, analyzing the behavior of NO concentration during solar storm and solar cycle can provide valuable insights into thermospheric energy balance, improving storm-time and climatological knowledge. In this study, we used newly calculated NO cooling rates and simulations of neutral kinetic temperature and atomic oxygen number density from the MSIS 2.1 model to derive 20-year NO concentration data. The global annual mean NO concentration shows a strong correlation with the solar cycle, with high concentrations and upper boundaries up to 250 km during solar maximum years and lower concentrations and upper boundaries up to ~230 km during solar minimum years. We also compared NO concentrations obtained from SABER measurements and MSIS 2.1 simulations during solar maximum (2014) and solar minimum (2009) years and found good agreement between the two during both day and night.

Ningchao Wang↗
NASA NTRS1983

Solar maximum repair mission

The Solar Maximum Repair Mission is scheduled for launch in April, 1984. The mission was made possible through a spacecraft designed for on-orbit repair, the availability of spacecraft repair hardware and the availability of the Shuttle System. Repair is expected to result in the availability of significant new science data and a demonstration of the capability for on-orbit repair of spacecraft. Considerations of the capability to maintain and repair spacecraft on-orbit for the future are also discussed.

Space transportation system↗