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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Path Forward to Space Solar Power using the O'Neill - Glaser Model Modified for Climate Change Demand and Considering the Increasing Risk of Human Self-Extinction if Confined to Earth

The cost of energy is humanity's economic exchange rate with the universe. Space solar power is the first great step that our technological species has to utilize the energy of its star. The classic Peter Glaser Solar Power Satellite, SPS, and later designs collect a large area of solar energy in space and beam it back to Earth for use in the electric grid, but even with optimistic launch costs and technology innovation a clear economic path is not evident using Earth launch of SPS. O Neill in 1969 solved the transportation costs problem by a model that uses lunar and asteroid materials to build SPS and locates the labor force permanently in space (O Neill free space habitats). This solution closes the economics and predicts large profits after 17-35 years. However the costs of time have up to now prevented this solution. We discuss a strategy to move forward in SPS with the motivations to stop global warming and prevent human selfextinction. There are near term steps that can be taken that place us on this path forward. First, we must reevaluate the technologies for the classic model and update the parameters to current technology. As technological capability continues to increase exponentially, we need to understand when the monetary potential energy hills are small as the technology gets larger. But the chance for self-extinction, if humanity remains in a single vulnerable habitat, also increased exponentially with time. The path forward is to identify investment points while assessing the risks of non-action.

Curreri, Peter A.↗
NASA NTRS2014

Effects of High-Density Impacts on Shielding Capability

Spacecraft are shielded from micrometeoroids and orbital debris (MMOD) impacts to meet requirements for crew safety and/or mission success. In the past, orbital debris particles have been considered to be composed entirely of aluminum (medium-density material) for the purposes of MMOD shielding design and verification. Meteoroids have been considered to be low-density porous materials, with an average density of 1 g/cu cm. Recently, NASA released a new orbital debris environment model, referred to as ORDEM 3.0, that indicates orbital debris contains a substantial fraction of high-density material for which steel is used in MMOD risk assessments [Ref.1]. Similarly, an update to the meteoroid environment model is also under consideration to include a high-density component of that environment. This paper provides results of hypervelocity impact tests and hydrocode simulations on typical spacecraft MMOD shields using steel projectiles. It was found that previous ballistic limit equations (BLEs) that define the protection capability of the MMOD shields did not predict the results from the steel impact tests and hydrocode simulations (typically, the predictions from these equations were too optimistic). The ballistic limit equations required updates to more accurately represent shield protection capability from the range of densities in the orbital debris environment. Ballistic limit equations were derived from the results of the work and are provided in the paper.

Christiansen, Eric L.↗
NASA NTRS2014

Search for Gravitational Waves Associated with Gamma-Ray Bursts Detected by the Interplanetary Network

We present the results of a search for gravitational waves associated with 223 gamma ray bursts (GRBs) detected by the InterPlanetary Network (IPN) in 2005-2010 during LIGO's fifth and sixth science runs and Virgo's first, second, and third science runs. The IPN satellites provide accurate times of the bursts and sky localizations that vary significantly from degree scale to hundreds of square degrees. We search for both a well-modeled binary coalescence signal, the favored progenitor model for short GRBs, and for generic, unmodeled gravitational wave bursts. Both searches use the event time and sky localization to improve the gravitational wave search sensitivity as compared to corresponding all-time, all-sky searches. We find no evidence of a gravitational wave signal associated with any of the IPN GRBs in the sample, nor do we find evidence for a population of weak gravitational wave signals associated with the GRBs. For all IPN-detected GRBs, for which a sufficient duration of quality gravitational wave data are available, we place lower bounds on the distance to the source in accordance with an optimistic assumption of gravitational wave emission energy of 10(exp−2) solar mass c(exp 2) at 150 Hz, and find a median of 13 Mpc. For the 27 short-hard GRBs we place 90% confidence exclusion distances to two source models: a binary neutron star coalescence, with a median distance of 12 Mpc, or the coalescence of a neutron star and black hole, with a median distance of 22 Mpc. Finally, we combine this search with previously published results to provide a population statement for GRB searches in first-generation LIGO and Virgo gravitational wave detectors and a resulting examination of prospects for the advanced gravitational wave detectors.

gravitational wave detectors↗
NASA NTRS2015

The AgMIP GRIDded Crop Modeling Initiative (AgGRID) and the Global Gridded Crop Model Intercomparison (GGCMI)

Climate change is a significant risk for agricultural production. Even under optimistic scenarios for climate mitigation action, present-day agricultural areas are likely to face significant increases in temperatures in the coming decades, in addition to changes in precipitation, cloud cover, and the frequency and duration of extreme heat, drought, and flood events (IPCC, 2013). These factors will affect the agricultural system at the global scale by impacting cultivation regimes, prices, trade, and food security (Nelson et al., 2014a). Global-scale evaluation of crop productivity is a major challenge for climate impact and adaptation assessment. Rigorous global assessments that are able to inform planning and policy will benefit from consistent use of models, input data, and assumptions across regions and time that use mutually agreed protocols designed by the modeling community. To ensure this consistency, large-scale assessments are typically performed on uniform spatial grids, with spatial resolution of typically 10 to 50 km, over specified time-periods. Many distinct crop models and model types have been applied on the global scale to assess productivity and climate impacts, often with very different results (Rosenzweig et al., 2014). These models are based to a large extent on field-scale crop process or ecosystems models and they typically require resolved data on weather, environmental, and farm management conditions that are lacking in many regions (Bondeau et al., 2007; Drewniak et al., 2013; Elliott et al., 2014b; Gueneau et al., 2012; Jones et al., 2003; Liu et al., 2007; M¨uller and Robertson, 2014; Van den Hoof et al., 2011;Waha et al., 2012; Xiong et al., 2014). Due to data limitations, the requirements of consistency, and the computational and practical limitations of running models on a large scale, a variety of simplifying assumptions must generally be made regarding prevailing management strategies on the grid scale in both the baseline and future periods. Implementation differences in these and other modeling choices contribute to significant variation among global-scale crop model assessments in addition to differences in crop model implementations that also cause large differences in site-specific crop modeling (Asseng et al., 2013; Bassu et al., 2014).

climate↗
NASA NTRS2015

Underestimation of Project Costs

Large projects almost always exceed their budgets. Estimating cost is difficult and estimated costs are usually too low. Three different reasons are suggested: bad luck, overoptimism, and deliberate underestimation. Project management can usually point to project difficulty and complexity, technical uncertainty, stakeholder conflicts, scope changes, unforeseen events, and other not really unpredictable bad luck. Project planning is usually over-optimistic, so the likelihood and impact of bad luck is systematically underestimated. Project plans reflect optimism and hope for success in a supposedly unique new effort rather than rational expectations based on historical data. Past project problems are claimed to be irrelevant because "This time it's different." Some bad luck is inevitable and reasonable optimism is understandable, but deliberate deception must be condemned. In a competitive environment, project planners and advocates often deliberately underestimate costs to help gain project approval and funding. Project benefits, cost savings, and probability of success are exaggerated and key risks ignored. Project advocates have incentives to distort information and conceal difficulties from project approvers. One naively suggested cure is more openness, honesty, and group adherence to shared overall goals. A more realistic alternative is threatening overrun projects with cancellation. Neither approach seems to solve the problem. A better method to avoid the delusions of over-optimism and the deceptions of biased advocacy is to base the project cost estimate on the actual costs of a large group of similar projects. Over optimism and deception can continue beyond the planning phase and into project execution. Hard milestones based on verified tests and demonstrations can provide a reality check.

Cost estimation↗
NASA NTRS2016

What Can We Learn From Proton Recoils about Heavy-Ion SEE Sensitivity?

The fact that protons cause single-event effects (SEE) in most devices through production of light-ion recoils has led to attempts to bound heavy-ion SEE susceptibility through use of proton data. Although this may be a viable strategy for some devices and technologies, the data must be analyzed carefully and conservatively to avoid over-optimistic estimates of SEE performance. We examine the constraints that proton test data can impose on heavy-ion SEE susceptibility.

probabilistic risk assessment↗
NASA NTRS2016

The Potential for Ambient Plasma Wave Propulsion

A truly robust space exploration program will need to make use of in-situ resources as much as possible to make the endeavor affordable. Most space propulsion concepts are saddled with one fundamental burden; the propellant needed to produce momentum. The most advanced propulsion systems currently in use utilize electric and/or magnetic fields to accelerate ionized propellant. However, significant planetary exploration missions in the coming decades, such as the now canceled Jupiter Icy Moons Orbiter, are restricted by propellant mass and propulsion system lifetimes, using even the most optimistic projections of performance. These electric propulsion vehicles are inherently limited in flexibility at their final destination, due to propulsion system wear, propellant requirements, and the relatively low acceleration of the vehicle. A few concepts are able to utilize the environment around them to produce thrust: Solar or magnetic sails and, with certain restrictions, electrodynamic tethers. These concepts focus primarily on using the solar wind or ambient magnetic fields to generate thrust. Technically immature, quasi-propellantless alternatives lack either the sensitivity or the power to provide significant maneuvering. An additional resource to be considered is the ambient plasma and magnetic fields in solar and planetary magnetospheres. These environments, such as those around the Sun or Jupiter, have been shown to host a variety of plasma waves. Plasma wave propulsion takes advantage of an observed astrophysical and terrestrial phenomenon: Alfven waves. These are waves that propagate in the plasma and magnetic fields around and between planets and stars. The generation of Alfven waves in ambient magnetic and plasma fields to generate thrust is proposed as a truly propellantless propulsion system which may enable an entirely new matrix of exploration missions. Alfven waves are well known, transverse electromagnetic waves that propagate in magnetized plasmas at frequencies below the ion cyclotron frequency. They have been observed in both laboratory and astrophysical settings. On Earth, they are being investigated as a possible means for plasma heating, current drive, and momentum addition in magnetic confinement fusion systems. In addition, Alfven waves have been proposed as a mechanism for acceleration of the solar wind away from the sun.

THE POTENTIAL FOR AMBIENT PLASMA WAVE PROPULSION↗
NASA NTRS2015

Lower Limits on Aperture Size for an ExoEarth Detecting Coronagraphic Mission

The yield of Earth-like planets will likely be a primary science metric for future space-based missions that will drive telescope aperture size. Maximizing the exoEarth candidate yield is therefore critical to minimizing the required aperture. Here we describe a method for exoEarth candidate yield maximization that simultaneously optimizes, for the first time, the targets chosen for observation, the number of visits to each target, the delay time between visits, and the exposure time of every observation. This code calculates both the detection time and multiwavelength spectral characterization time required for planets. We also refine the astrophysical assumptions used as inputs to these calculations, relying on published estimates of planetary occurrence rates as well as theoretical and observational constraints on terrestrial planet sizes and classical habitable zones. Given these astrophysical assumptions, optimistic telescope and instrument assumptions, and our new completeness code that produces the highest yields to date, we suggest lower limits on the aperture size required to detect and characterize a statistically motivated sample of exoEarths.

Earth-like planets↗
NASA NTRS2018

Realistic Covariance Generation for the GPM Spacecraft

We present several different methods for generating realistic predictive covariance, including Monte-Carlo simulations and more direct linear methods which require the addition of process noise. The Monte-Carlo simulation starts with an epoch uncertainty sample basis and propagates each trial to a time of interest in the future. The variance-covariance of the state elements as well as other higher order sample statistics can be readily computed from the propagated sample. While this method preserves the nonlinear effects on the propagated uncertainty, it is computationally intensive as a statistically significant sample size must be considered in the propagation process. Moreover, if the epoch covariance is optimistic, this can result in an underestimation of the prediction error. Another method is to propagate a state sensitivity matrix simultaneously with the satellite state, which allows the epoch covariances to be propagated forward in a linear fashion. This method does not preserve the non-linearity of the satellite state uncertainty but is much less computationally intensive. The propagated state covariance is the scaled to represent the realistic level of GPM state uncertainty via a "e-tuning process." The tuning process generates an inflation factor based on the observed error statistics of the predictive satellite trajectories when compared to the definitive ones. Difference tuning strategies are considered and compared via Goodness-of-Fit method testing for the Gaussian properties of the scaled covariance.

prediction error↗
NASA NTRS2017

Characterizing K2 Candidate Planetary Systems Orbiting Low-Mass Stars. II. Planetary Systems Observed During Campaigns 1-7

We recently used near-infrared spectroscopy to improve the characterization of 76 low-mass stars around which K2 had detected 79 candidate transiting planets. 29 of these worlds were new discoveries that had not previously been published. We calculate the false positive probabilities that the transit-like signals are actually caused by non-planetary astrophysical phenomena and reject five new transit-like events and three previously reported events as false positives. We also statistically validate 17 planets (7 of which were previously unpublished), confirm the earlier validation of 22 planets, and announce 17 newly discovered planet candidates. Revising the properties of the associated planet candidates based on the updated host star characteristics and refitting the transit photometry, we find that our sample contains 21 planets or planet candidates with radii smaller than 1.25 solar radii, 18 super-Earths (1.25-2 solar radii), 21 small Neptunes (2-4 solar radii), three large Neptunes (4-6 solar radii), and eight giant planets (greater than 6 solar radii). Most of these planets are highly irradiated, but EPIC 206209135.04 (K2-72e, 1.29 from plus 0.19 to minus 0.18 solar radii), EPIC 211988320.01 (perihelion radius equals 2.86 from plus 0.16 to minus 0.15 solar radii), and EPIC 212690867.01 (2.20 from plus 0.19 to minus 0.18 solar radii) orbit within optimistic habitable zone boundaries set by the "recent Venus" inner limit and the "early Mars" outer limit. In total, our planet sample includes eight moderately irradiated 1.5-3 solar radii planet candidates (planetary flux greater than or approximately 20 times Earth's flux) orbiting brighter stars (Ks less than 11) that are well-suited for atmospheric investigations with the Hubble, Spitzer, and/or James Webb Space Telescopes. Five validated planets orbit relatively bright stars (Kp less than 12.5) and are expected to yield radial velocity semi-amplitudes of at least 2 meters per second. Accordingly, they are possible targets for radial velocity mass measurement with current facilities or the upcoming generation of red optical and near-infrared high-precision RV (Radial Velocity) spectrographs.

Dressing, Courtney D.↗
NASA NTRS2018

A Prognostic Launch Vehicle Probability of Failure Assessment Methodology for Conceptual Systems Predicated on Human Causal Factors

Create an improved method to calculate reliability of a conceptual launch vehicle system prior to fabrication by using historic data of actual root causes of failures. While failures have unique "proximate causes", there are typically a finite amount of common "root causes". Heretofore launch vehicle reliability evaluation typically hardware-centric statistical analyses, while most root causes of failures are been shown to be human-centric. A method based on human-centric root causes can be used to quantify reliability assessments and focus proposed actions to mitigate problems. Existing methods have been optimistic in their projections of launch vehicle reliability compared to actuals. Hypothesis: reliability of a conceptual launch vehicle can be more accurately evaluated based on a rational, probabilistic approach using past failure assessment teams' findings predicated on human-centric causes."Human Reliability Analysis Methods Selection Guidance for NASA"Chandler F.T., et al., NASA HQ/OSMA study group, July 2006. Outside HRA experts from academia, other federal labs, and the private sector. 50 system reliability methods considered, fourteen selected for further study, four finally selected as best suited for human spaceflight. Probabilistic Risk Analysis (PRA) + Human Reliability Analysis (HRA) enabled incorporating effects and probabilities of human errors. While four down-selected methods deemed appropriate for failure assessment, it did not appear that these methods could be concisely applied to perform major system-wide assessment of probability of failure of a conceptual design without becoming unwieldy."Engineering a Safer World", Detailed, comprehensive study external to NASA Leveson N. G., MIT, 2011.Systems-Theoretic Accident Model and Processes (STAMP). All-encompassing accident model based on systems theory analyzed accidents after they occurred and created approaches to prevent occurrence in developing systems not focused on failure prevention per se, but rather reducing hazards by influencing human behavior through use of constraints, hierarchical control structures, and process models to improve system safetySystem Theoretic Process Analysis (STPA) addresses predictive part of problem (a "hazard analysis"). Includes all causal factors identified in STAMP: "...design errors, software flaws, component interaction accidents, cognitively complex human decision-making errors, and social organizational and management factors contributing to accidents" can guide design process rather than require it to exist before-hand did not appear capable of concise application for system-wide assessment of probability of failure of a conceptual design without becoming unwieldy.

Williams, Craig H.↗
NASA NTRS2018

The Impact of Stellar Variability on the Detection of Transiting Earth-like Planets

Stellar variability represents a key limitation on the detectability of weak transit signatures of small, Earth-size planets with space-based missions such as NASA's Kepler Mission or ESA's PLATO Mission. The expectations for the performance of the Kepler Mission in the face of solar-like variability were predicated on observations of the Sun with the Variability of Solar Irradiance and Gravity Oscillations (VIRGO) instrument aboard NASA and ESA's joint Solar and Heliospheric Observatory (SOHO) mission, which was launched in December 1995. Analyses of SOHO data indicated that solar-like variability would contribute approx.10 ppm to Kepler's noise budget at 6.5 ours, a typical grazing transit timescale. This proved to be optimistic as the typical 12th mag G2V star in the Kepler field of view exhibited 20 ppm of stellar variability-related noise at 6.5 hours, making the detection of true Earth-Sun analogs more difficult. While the consequent increase in the total noise at 6.5 hours from 20 ppm to 30 ppm could have been overcome by extending the mission to a total duration of 7 to 8 years. Unfortunately, a second reaction wheel failed in May 2013, ending the Kepler primary mission. Nevertheless, Kepler proved to be a veritable cornucopia of science results, both for exoplanets and for astrophysics. The phenomenal photometric precision and continuous observations required in order to identify small, rocky transiting planets enables the study of a large range of phenomena contributing to stellar variability for many thousands of solar-like stars in Kepler's field of view in exquisite detail. These effects range from less than 1 ppm acoustic oscillations on timescales from a few minutes and longward, to flares on timescales of hours, to spot-induced modulation on timescales of days to weeks to activity cycles on timescales of months to years. Kepler discovered over 2600 validated and confirmed exoplanets, and measured the pressure-mode oscillations of over 15000 stars over the course of its mission and the reconstituted K2 mission. We present the adaptive, wavelet-based matched filter used for both the Kepler and the TESS missions, and discuss the connections between this detection algorithm and fundamental detection theory, which allows the detector to function as a noise characterization engine. This provides a dynamical measurement of the photometric noise at transit timescales and thus, a key performance metric for missions like PLATO and Kepler. We give an overview of the stellar variability we see across the full range of spectral types observed by Kepler, from the cool, small red M stars to the hot, large late A stars, both in terms of amplitude as well as timescale.

transit surveys↗
NASA NTRS2019

High Reliability Requires More than Providing Spares

It is sometimes optimistically hoped that a space life support system can be kept working throughout a long duration mission by repairing failed components, as long as sufficient spares are flown. It is usually assumed that the components have constant known failure rates. Then the needed numbers of spares can be computed to have any particular probability that all failed components can be replaced by available spares. This approach can provide high reliability if its favorable assumptions, including constant known failure rates, are satisfied. Other favorable assumptions are that the failures are statistically independent, repair will be successful without causing further failures, and all failures are due to internal component failures. These assumptions are not usually justified. The failure rates may be estimates that are inadequately verified because of insufficient testing. Failure rates may change due to materials substitutions, manufacturing changes, redesigns to fix failures, and new failures caused by redesigns. Failures that are not statistically independent may result from one common cause, such as a design or manufacturing error or a cascade of cause and effect, possibly caused by an external event such as a power outage. Repair may be unsuccessful or cause damage. Many failures occur at component interfaces or at the overall systems level, not within isolated components. Other failures causes are completely external to the system, due to assembly, maintenance, and operational errors or to unexpected environmental challenges. Replacement with sufficient spares can compensate for expected internal component failures but may not be able to cope with unpredictable design and manufacturing flaws, human errors, and environmental impacts. Reliability estimates based on providing sufficient spares to compensate for expected failures may be far too high. They are essentially upper bounds on reliability that might be approached if many frequent but often unconsidered failure causes can be eliminated.

spares↗
NASA NTRS2018

The Impact of Stellar Variability on the Detection of Transiting Earth-Like Planets

Stellar variability represents a key limitation on the detectability of weak transit signatures of small, Earth-size planets with space-based missions such as NASA's Kepler Mission or ESA's PLATO Mission. The expectations for the performance of the Kepler Mission in the face of solar-like variability were predicated on observations of the Sun with the Variability of Solar Irradiance and Gravity Oscillations (VIRGO) instrument aboard NASA and ESA's joint Solar and Heliospheric Observatory (SOHO) mission, which was launched in December 1995. Analyses of SOHO data indicated that solar-like variability would contribute ~10 ppm to Kepler's noise budget at 6.5 ours, a typical grazing transit timescale. This proved to be optimistic as the typical 12th mag G2V star in the Kepler field of view exhibited 20 ppm of stellar variability-related noise at 6.5 hours, making the detection of true Earth-Sun analogs more difficult. While the consequent increase in the total noise at 6.5 hours from 20 ppm to 30 ppm could have been overcome by extending the mission to a total duration of 7 to 8 years. Unfortunately, a second reaction wheel failed in May 2013, ending the Kepler primary mission. Nevertheless, Kepler proved to be a veritable cornucopia of science results, both for exoplanets and for astrophysics. The phenomenal photometric precision and continuous observations required in order to identify small, rocky transiting planets enables the study of a large range of phenomena contributing to stellar variability for many thousands of solar-like stars in Kepler's field of view in exquisite detail. These effects range from <1 ppm acoustic oscillations on timescales from a few minutes and longward, to flares on timescales of hours, to spot-induced modulation on timescales of days to weeks to activity cycles on timescales of months to years. Kepler discovered over 2600 validated and confirmed exoplanets, and measured the pressure-mode oscillations of over 15000 stars over the course of its mission and the reconstituted K2 mission. We present the adaptive, wavelet-based matched filter used for both the Kepler and the TESS missions, and discuss the connections between this detection algorithm and fundamental detection theory, which allows the detector to function as a noise characterization engine. This provides a dynamical measurement of the photometric noise at transit timescales and thus, a key performance metric for missions like PLATO and Kepler. We give an overview of the stellar variability we see across the full range of spectral types observed by Kepler, from the cool, small red M stars to the hot, large late A stars, both in terms of amplitude as well as timescale.

exoplanets↗
NASA NTRS2019

Fusion-Enabled Pluto Orbiter and Lander

Direct Fusion Drive (DFD) is a unique fusion engine concept based on the Princeton Field-Reversed Configuration (PFRC) fusion reactor conceived by Dr. Sam Cohen of the Princeton Plasma Physics Laboratory. DFD would enable the Pluto orbiter and lander context mission and more broadly enable true "rapid transit" to outer-planet and near interstellar space. The truly game-changing levels of thrust and power in a modestly sized package could integrate with our current launch infrastructure while radically expanding the science capability of these missions. Our Phase I was our first funded work on the DFD, with previous work at PSS occurring only under internal R&D. We established the feasibility of our Pluto mission trajectories using straight-line and planar models, including a departure spiral from Earth and insertion at Pluto. We developed our first thrust and specific impulse model using the results of the UEDGE multi-fluid code. Our specific power model was improved. During this Phase II effort, we continued our efforts to increase the fidelity of the designs for the RF, magnet, and shielding subsystems. Dedicated thrust augmentation experiments were run on the PFRC experiment, using a supersonic gas puffing valve. For the first time, we analyzed the design of a closed-loop operation mode and estimated the hardware that would be required for a dual-mode engine. In an exciting new development, we have invented a new thermophotovoltaic thermal conversion method that has the potential to have efficiencies of a Brayton or Stirling system. Our report presents details of these analyses. Our roadmap to bringing DFD to flight predicts that with sufficient support, a first flight unit could be built by 2040. We anticipate that three machine generations are required before this point: a ~1 T PFRC-3 machine hitting new plasma temperature and density levels, a ~5 T PFRC-4 machine with first demonstration of D-3He fusion, and a flight. (The current experiment, PFRC-2, is limited to about 0.1 T). In order to achieve a flight in 2035-2040, the TRL of the supporting systems must be increased in parallel, including low mass radiators, cryogenic propellant storage, and large (>100 kW) thermal conversion systems. Fortunately, many of these systems are dual-use and are required for other technologies including fission systems, so DFD would contribute to and benefit from those programs. This NIAC support and the results of our work have led to multiple follow-on contracts. We won two NASA STTRs focused on DFD subsystems, one on the RF system and one on the superconducting magnets, and our magnet STTR is now midway through a Phase II. We will be receiving a superconducting test magnet for experiments at PPPL this summer. In addition, we won an ARPA-E OPEN grant; this is the first time that OPEN has included fusion technologies, and we are part of a cohort of three alternative fusion companies now supported directly by DOE. We are very optimistic that if we are able to meet our experimental milestones in the next 12-18 months, we will be competitive for additional DOE grants to build PFRC-3.

Propulsion↗
NASA NTRS2019

Space Program Advocacy Can Distort Project Management and Damage Systems Engineering

Over-optimistic project advocacy often causes exaggerated performance claims and underestimated costs and schedules. This can distort project management and damage systems engineering. NASA projects such as the space shuttle and Hubble are extreme examples. NASA's spectacular success in the Apollo moon landings seems to have produced overconfidence and carelessness, but also to have gained tolerance for unrealistic claims and forgiveness when they were proven wrong. Apollo risk analysis predicted many astronaut fatalities. This was believed but was potentially damaging to the Apollo program, so risk analysis was discontinued. The moon landings beat bad odds because Apollo obsessively reduced risk. Its success seemed to confirm that risk analysis was unreasonably pessimistic and that risk could be overcome by good engineering. This understanding caused risk to be increased during space shuttle engineering and led to an unnecessarily dangerous approach. The shuttle design placed a fragile spacecraft next to the fuel tanks and failed to provide crew escape or launch abort. These design decisions directly caused the Challenger and Columbia tragedies. After Challenger, risk analysis was re-established. The current rocket and capsule design does consider risk and the result strongly resembles Apollo. Apollo advocacy led NASA to abandon risk analysis and this was ultimate cause of the Shuttle tragedies. Excessive advocacy that distorts risk, cost, and schedule could be prevented in an ideal organization that used systems engineering to make rational and fair decisions. However, most real organizations accommodate human and group needs using informal methods often described as "the system." Humans have biases, use innate decision making heuristics, instinctively rely on "gut feel," and establish deviant groups through groupthink. Expecting organizations to become totally rational is impractical, but specific problems such as neglecting risk and underestimating cost and schedule can be directly challenged with some hope of success.

Jones, Harry W.↗
NASA NTRS2020

Possible Climate Histories of Venus Type Worlds

There are two well-known scenarios for Venus’ climate evolution. In one Venus had a long-lived magma ocean phase in its first 100Myr with a steam and CO2 dominated atmosphere. The faint young sun with its high XUV flux would cause photodissociation of the steam atmosphere and hydrodynamic escape would cause most of the hydrogen to escape & left-over oxygen would be absorbed by the magma ocean. Hence Venus would have started out hot and dry and the high D/H ratio measured by Pioneer Venus would be from this period of water loss. The other scenario is that Venus’ magma ocean lifetime would have been roughly the same length of time as Earth’s (~1Myr) and water would have condensed on its surface in its early history and had a short period of habitability before increasing solar insolation through time drove it into a runaway greenhouse. However, results from 2016 showed that if Venus remains in the slowly rotating climate dynamics regime (as seen in exoplanet related climate studies) its cloud albedo feedback would have kept it temperate for possibly billions of years. The only way to confirm which one of these scenarios occurred for Venus is to visit it and make the necessary measurements of noble and volatile gases. But exoplanet observations of young exo-Venus type worlds around young F,G,K dwarf stars may constrain which scenario is more probable for a population of such planets. We present a vision of Venus’ climate history that places it and its exoVenus cousins in an ‘Optimistic Venus Zone’ for ~3 billion years within the conventionally named ‘Venus Zone’ and hence encourage the exoplanet communit as possible habitable environments.

Way, M. J.↗
NASA NTRSDate not supplied

Lessons from Earth Bioaerosol Sampling for Venus Habitability & Biosignature Science

Venus’s clouds are often discussed as a potential habitat. Several high-priority science goals – cloud aerosol composition, internal radiative flux, and aerosol residence time and circulation models – will improve our understanding of Venus in an astrobiology context. Lessons from Earth’s aerobiosphere can inform these requirements and interpretation of results. A stable Venus aerobiosphere would need microorganisms to reproduce faster than they settle out due to gravity. This is a joint constraint of the potential nutrients and energy influx, bioenergetic costs such as desiccation and radiation damage, and aerosol dynamics. Though life cycles involving S- and Fe-based redox metabolism have been proposed, at an optimistic estimate of 75% H2SO4, Venus aerosol water activity (aw) is still ~0.02, far below the observed microbial growth limit of ~0.6. Long-term desiccation with brief spurts of repair, growth and reproduction in response to transient water influx (perhaps volcanism) is the most likely model for Earth-like life on Venus – a ‘desert bloom’ scenario. In Earth’s troposphere, clouds can carry 103 – 105 cells/mL, some metabolically active. A better analogue may be Earth’s stratospheric sulfate aerosol layer: supercooled sulfuric acid aerosols (acid weight fraction 0.6 – 0.85, 0.1 – 1 µm diameter, 0.1 – 1 cm-3) with little water activity, long residence times, high UV radiation, and only sporadic influx from surface particle sources. Viable cells isolated from this region are rare (~102 cells/m3), though ‘hot spots’ at tropospheric mixing occur. Cells are primarily in inactive forms such as spores, and it is unclear if any are associated with sulfate aerosols or simply co-located. Given the heterogeneities in Venus clouds and the model of a sparse, largely dormant ecosystem, a single transect on descent would most likely pass through a low-water, inactive region, missing potential signs of habitability or biosignatures. Even a passive aerial platform (balloon) may end up following a single air mass over its lifetime. A better strategy for Venus would target an aerial region with some upwelling from surface sources, and take multiple transects separated in time and space. Earth’s stratospheric bioaerosol population could provide a starting point for estimating the required lower volume and detection limits.

Earth↗