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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 NTRS2017

STEREO Superior Solar Conjunction Mission Phase

With its long duration and high gain antenna (HGA) feed thermal constraint; the NASA Solar-TErestrial RElations Observatory (STEREO) solar conjunction mission phase is quite unique to deep space operations. Originally designed for a two year heliocentric orbit mission to primarily study coronal mass ejection propagation, after 8 years of continuous science data collection, the twin STEREO observatories entered the solar conjunction mission phase, for which they were not designed. Nine months before entering conjunction, an unforeseen thermal constraint threatened to stop daily communications and science data collection for 15months. With a 3.5 month long communication blackout from the superior solar conjunction, without ground commands, each observatory will reset every 3 days, resulting in 35 system resets at an Earth range of 2 AU. As the observatories will be conjoined for the first time in 8 years, a unique opportunity for calibrating the same instruments on identical spacecraft will occur. As each observatory has lost redundancy, and with only a limited fidelity hardware simulator, how can the new observatory configuration be adequately and safely tested on each spacecraft? Without ground commands, how would a 3-axis stabilized spacecraft safely manage the ever accumulating system momentum without using propellant for thrusters? Could science data still be collected for the duration of the solar conjunction mission phase? Would the observatories survive? In its second extended mission, operational resources were limited at best. This paper discusses the solutions to the STEREO superior solar conjunction operational challenges, science data impact, testing, mission operations, results, and lessons learned while implementing.

STEREO↗
DOE OSTI2021

Quantifying Uncertainty in All-to-All Estimates of Space Object Conjunction Probabilities using U-Statistics

Predicting space object conjunctions is inherently probabilistic due to initial state and orbit model uncertainty. A commonly considered Monte Carlo estimator of the conjunction probability is the ’all-to-all’ estimator. Given independent random samples of the trajectories of both objects, the estimator is the percentage of all pairs of trajectories that result in a conjunction. Intuitively, the all-to-all estimator is the best possible estimator of the conjunction probability since it considers all pairs of Monte Carlo samples. However, its distribution is not available in closed-form, which limits its use in practice and makes this intuition difficult to make rigorous. In this paper, the all-to-all estimator is identified as a U-statistic, which implies that it has several favorable properties. Specifically, the estimator is the minimum variance unbiased estimator of the conjunction probability and is asymptotically Gaussian distributed. An approximate confidence interval for the conjunction probability is obtained from an estimate of the asymptotic Gaussian distribution. We show how to efficiently compute the confidence interval and demonstrate that the interval has the nominal coverage level. The confidence intervals are also seen to be narrower than those based on the commonly-used each-to-each estimator. Furthermore, the all-to-all estimator is shown to allow different Monte Carlo sample sizes, whereas the each-to-each estimator requires equal sample sizes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2011

Assessment of Uncertainty-Based Screening Volumes for NASA Robotic LEO and GEO Conjunction Risk Assessment

Conjunction Assessment operations require screening assets against the space object catalog by placing a pre-determined spatial volume around each asset and predicting when another object will violate that volume. The selection of the screening volume used for each spacecraft is a trade-off between observing all conjunction events that may pose a potential risk to the primary spacecraft and the ability to analyze those predicted events. If the screening volumes are larger, then more conjunctions can be observed and therefore the probability of a missed detection of a high risk conjunction event is small; however, the amount of data which needs to be analyzed increases. This paper characterizes the sensitivity of screening volume size to capturing typical orbit uncertainties and the expected number of conjunction events observed. These sensitivities are quantified in the form of a trade space that allows for selection of appropriate screen-ing volumes to fit the desired concept of operations, system limitations, and tolerable analyst workloads. This analysis will specifically highlight the screening volume determination and selection process for use in the NASA Conjunction Assessment Risk Analysis process but will also provide a general framework for other Owner / Operators faced with similar decisions.

Narvet, Steven W.↗
NASA NTRS2015

Collision Avoidance Short Course: Conjunction Assessment Risk Analysis - NASA Robotic CARA: Theory - Part I:

Satellite conjunction assessment is perhaps the fastest growing area in space situational awareness and protection with military, civil and commercial satellite owner-operators embracing more and more sophisticated processes to avoid the avoidable - namely collisions between high value space assets and orbital debris. NASA and Centre National d'Etudes Spatiales (CNES) have collaborated to offer an introductory short course on all the major aspects of the conjunctions assessment problem. This half-day course will cover satellite conjunction dynamics and theory. Joint Space Operations Center (JsPOC) conjunction data products, major risk assessment parameters and plots, conjunction remediation decision support, and present and future challenges. This briefing represents the NASA portion of the course.

Conjunction↗
NASA NTRSDate not supplied

Deep-Space Conjunction Assessment: Recent Developments and Future Evolution

The Multi-mission Automated Deep-space Conjunction Assessment Process (MADCAP) is a NASA Jet Propulsion Laboratory (JPL) capability used to perform conjunction assessment in shared deep-space environments. MADCAP began performing conjunction assessment at Mars and the Moon in 2011, with the Sun/Earth libration points added to its functionality in 2020. There has been an increasing number of missions operating in these environments in recent years, leading to an elevated frequency of close conjunction events, especially in the Lunar orbital environment. MADCAP provides this service not only to NASA missions, but to any operator who is willing to share ephemerides. Since there is no space surveillance network for deep space environments, ephemeris sharing is the only way in which spacecraft operators can ensure the safety of their spacecraft from collision in these orbit regimes. NASA published a set of conjunction assessment best practices in 2020 that cover the MADCAP process. This paper details recent MADCAP operational experience in the deep space environments, including statistics and process improvements. Updates to the MADCAP software and automation framework implemented to handle the recent growth in the number of deep space missions are also discussed. Future enhancements planned in anticipation of increasingly crowded deep-space environments, such as non-standard runs based on exploratory scenarios, are also discussed.

conjunction assessment↗
DOE OSTI2021

Evaluating Space Object Conjunction Probabilities Using Characteristic Function Inversion

This report discusses an approach to computing the probability of a conjunction between two space objects in the short-term encounter scenario. A conjunction is defined here as an event where the miss distance between the objects is less than some specified value. The scenario assumptions are that the motion of the objects is linear, their positions are Gaussian distributed, and their velocities are known and constant. Under these assumptions, the squared-miss distance is shown to have the generalized chi-square distribution. An established statistical technique called characteristic function inversion is employed to evaluate the distribution and obtain conjunction probabilities. The method is closely related to a recent approach based on moment generating function inversion, and a qualitative comparison of the approaches is provided. Last, the method is tested on several benchmark test cases where it agrees with numerical integration on the cases with conjunction probabilities above 10 –12 . However, the exact probability in these cases is usually not needed and this probability can be bounded above using an independent Gaussian approximation. Overall, the report shows how to compute conjunction probabilities using a standard statistical method, though numerical integration seems to perform equally well.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2009

A Single Conjunction Risk Assessment Metric: the F-Value

The Conjunction Assessment Team at NASA Goddard Space Flight Center provides conjunction risk assessment for many NASA robotic missions. These risk assessments are based on several figures of merit, such as miss distance, probability of collision, and orbit determination solution quality. However, these individual metrics do not singly capture the overall risk associated with a conjunction, making it difficult for someone without this complete understanding to take action, such as an avoidance maneuver. The goal of this analysis is to introduce a single risk index metric that can easily convey the level of risk without all of the technical details. The proposed index is called the conjunction "F-value." This paper presents the concept of the F-value and the tuning of the metric for use in routine Conjunction Assessment operations.

Frigm, Ryan Clayton↗
NASA NTRS2017

Time Dependence of Collision Probabilities During Satellite Conjunctions

The NASA Conjunction Assessment Risk Analysis (CARA) team has recently implemented updated software to calculate the probability of collision (P (sub c)) for Earth-orbiting satellites. The algorithm can employ complex dynamical models for orbital motion, and account for the effects of non-linear trajectories as well as both position and velocity uncertainties. This “3D P (sub c)” method entails computing a 3-dimensional numerical integral for each estimated probability. Our analysis indicates that the 3D method provides several new insights over the traditional “2D P (sub c)” method, even when approximating the orbital motion using the relatively simple Keplerian two-body dynamical model. First, the formulation provides the means to estimate variations in the time derivative of the collision probability, or the probability rate, R (sub c). For close-proximity satellites, such as those orbiting in formations or clusters, R (sub c) variations can show multiple peaks that repeat or blend with one another, providing insight into the ongoing temporal distribution of risk. For single, isolated conjunctions, R (sub c) analysis provides the means to identify and bound the times of peak collision risk. Additionally, analysis of multiple actual archived conjunctions demonstrates that the commonly used “2D P (sub c)” approximation can occasionally provide inaccurate estimates. These include cases in which the 2D method yields negligibly small probabilities (e.g., P (sub c)) is greater than 10 (sup -10)), but the 3D estimates are sufficiently large to prompt increased monitoring or collision mitigation (e.g., P (sub c) is greater than or equal to 10 (sup -5)). Finally, the archive analysis indicates that a relatively efficient calculation can be used to identify which conjunctions will have negligibly small probabilities. This small-P (sub c) screening test can significantly speed the overall risk analysis computation for large numbers of conjunctions.

Hall, Doyle T.↗
NASA NTRS2019

Assessing GEO and LEO Repeating Conjunctions Using High Fidelity Brute Force Monte Carlo Simulations

Probability of collision (P(sub c)) estimates for Earth-orbiting satellites typically assume a temporally-isolated conjunction event. However, under certain conditions two objects may experience multiple high-risk close approach events over the course of hours or days. In these repeating conjunction cases, the P(sub c) accumulates as each successive encounter occurs. The NASA Conjunction Assessment Risk Analysis team has updated its “brute force Monte Carlo” (BFMC) software to estimate such accumulating P(sub c) values for repeating conjunctions. This study describes the updated BFMC algorithm and discusses the implications for conjunction risk assessment.

Baars, Luis↗
NASA NTRS2019

Assessing Geo and Leo Repeating Conjunctions Using High Fidelity Brute Force Monte Carlo Simulations

Probability of collision (P(sub c)) estimates for Earth-orbiting satellites typically assume a temporally-isolated conjunction event. However, under certain conditions two objects may experience multiple high-risk close approach events over the course of hours or days. In these repeating conjunction cases, the P(sub c) accumulates as each successive encounter occurs. The NASA Conjunction Assessment Risk Analysis team has updated its “brute force Monte Carlo” (BFMC) software to estimate such accumulating P(sub c) values for repeating conjunctions. This study describes the updated BFMC algorithm and discusses the implications for conjunction risk assessment.

Baars, Luis↗
NASA NTRS2019

Recommended Methods for Setting Mission Conjunction Analysis Hard Body Radii

For real-time conjunction assessment (CA) operations, computation of the Probability of Collision (P(sub c)) typically depends on the state vector, its covariance, and the combined hard body radius (HBR) of both the primary and secondary space-craft. However, most algorithmic approaches that compute the P(sub c) use generic conservatively valued HBRs that may tend to go beyond the physical limitations of both spacecraft, enough to drastically change the results of a conjunction assessment mitigation decision. On the other hand, if the attitude of the spacecraft is known and available, then a refined HBR can be obtained that could result in an improved and accurate numerically-computed P(sub c) value. The goal of this analysis is to demonstrate the various calculated P(sub c) values obtained based on a number of different HBR calculation techniques, oriented in the encounter or conjunction plane at the time of closest approach (TCA). Since in most conjunctions the secondary object is a debris object and thus orders of magnitude smaller than the primary, the greatest operational benefit is wrought by developing a better size estimate and representation for the primary object. We present an analysis that includes the attitude information of the primary object in the HBR calculation and assesses the resulting P(sub c) values for conjunction assessment decision making.

Mashiku, Alinda K.↗
NASA NTRS2019

Recommended Methods for Setting Mission Conjunction Analysis Hard Body Radii

For real-time conjunction assessment (CA) operations, computation of the Probability of Collision (P(sub c)) typically depends on the state vector, its covariance, and the combined hard body radius (HBR) of both the primary and secondary space-craft. However, most algorithmic approaches that compute the P(sub c) use generic conservatively valued HBRs that may tend to go beyond the physical limitations of both spacecraft, enough to drastically change the results of a conjunction assessment mitigation decision. On the other hand, if the attitude of the spacecraft is known and available, then a refined HBR can be obtained that could result in an improved and accurate numerically-computed P(sub c) value. The goal of this analysis is to demonstrate the various calculated P(sub c) values obtained based on a number of different HBR calculation techniques, oriented in the encounter or conjunction plane at the time of closest approach (TCA). Since in most conjunctions the secondary object is a debris object and thus orders of magnitude smaller than the primary, the greatest operational benefit is wrought by developing a better size estimate and representation for the primary object. We present an analysis that includes the attitude information of the primary object in the HBR calculation and assesses the resulting P(sub c) values for conjunction assessment decision making.

Mashiku, Alinda K.↗
DOE OSTI2016

Conjunctive management of surface and groundwater resources under projected future climate change scenarios

Our study introduces a mixed integer linear fractional programming (MILFP) method to optimize conjunctive use of future surface water and groundwater resources under projected climate change scenarios. The conjunctive management model maximizes the ratio of groundwater usage to reservoir water usage. Future inflows to the reservoirs were estimated from the future runoffs projected through hydroclimate modeling considering the Variable Infiltration Capacity model, and 11 sets of downscaled Coupled Model Intercomparison Project phase 5 global climate model projections. Bayesian model averaging was adopted to quantify uncertainty in future runoff projections and reservoir inflow projections due to uncertain future climate projections. Optimized conjunctive management solutions were investigated for a water supply network in northern Louisiana which includes the Sparta aquifer. Runoff projections under climate change scenarios indicate that runoff will likely decrease in winter and increase in other seasons. Ultimately, results from the developed conjunctive management model with MILFP indicate that the future reservoir water, even at 2.5% low inflow cumulative probability level, could counterbalance groundwater pumping reduction to satisfy demands while improving the Sparta aquifer through conditional groundwater head constraint.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

Total Probability of Collision as a Metric for Finite Conjunction Assessment and Collision Risk Management

On-orbit collision risk is becoming an increasing mission risk to all operational satellites in Earth orbit. Managing this risk can be disruptive to mission and operations, present challenges for decision-makers, and is time-consuming for all parties involved. With the planned capability improvements to detecting and tracking smaller orbital debris and capacity improvements to routinely predict on-orbit conjunctions, this mission risk will continue to grow in terms of likelihood and effort. It is very real possibility that the future space environment will not allow collision risk management and mission operations to be conducted in the same manner as it is today. This paper presents the concept of a finite conjunction assessment-one where each discrete conjunction is not treated separately but, rather, as a continuous event that must be managed concurrently. The paper also introduces the Total Probability of Collision as an analogous metric for finite conjunction assessment operations and provides several options for its usage in a Concept of Operations.

Conjunction Assessment↗
NASA NTRS1975

Analysis and prediction of Doppler noise during solar conjunctions

The results of a study of Doppler data noise during solar conjunctions were presented. During the first half of 1975, a sizeable data base of Doppler data noise (estimates) for the Pioneer 10, Pioneer 11, and Helios 1 solar conjunctions was accumulated. To analyze this data, certain physical assumptions are made, leading to the development of a geometric parameter ("ISI") which correlates strongly with Doppler data noise under varying sun-earth-spacecraft geometries. Doppler noise models are then constructed from this parameter, resulting in the newfound ability to predict Doppler data noise during solar conjunctions, and hence to additionally be in a position to validate Doppler data acquired during solar conjunctions.

Berman, A. L.↗
NASA NTRS1992

Conjunctive programming: An interactive approach to software system synthesis

This report introduces a technique of software documentation called conjunctive programming and discusses its role in the development and maintenance of software systems. The report also describes the conjoin tool, an adjunct to assist practitioners. Aimed at supporting software reuse while conforming with conventional development practices, conjunctive programming is defined as the extraction, integration, and embellishment of pertinent information obtained directly from an existing database of software artifacts, such as specifications, source code, configuration data, link-edit scripts, utility files, and other relevant information, into a product that achieves desired levels of detail, content, and production quality. Conjunctive programs typically include automatically generated tables of contents, indexes, cross references, bibliographic citations, tables, and figures (including graphics and illustrations). This report presents an example of conjunctive programming by documenting the use and implementation of the conjoin program.

Tausworthe, Robert C.↗
NASA NTRS2010

Assessment, Planning, and Execution Considerations for Conjunction Risk Assessment and Mitigation Operations

An operational Conjunction Assessment Risk Analysis (CARA) concept is the real-time process of assessing risk posed by close approaches and reacting to those risks if necessary. The most effective way to completely mitigate conjunction risk is to perform an avoidance maneuver. The NASA Goddard Space Flight Center has implemented a routine CARA process since 2005. Over this period, considerable experience has been gained and many lessons have been learned. This paper identifies and presents these experiences as general concepts in the description of the Conjunction Assessment, Flight Dynamics, and Flight Operations methodologies and processes. These general concepts will be tied together and will be exemplified through a case study of an actual high risk conjunction event for the Aura mission.

Frigm, Ryan C.↗
NASA NTRS2014

Trades Between Opposition and Conjunction Class Trajectories for Early Human Missions to Mars

Candidate human missions to Mars, including NASA's Design Reference Architecture 5.0, have focused on conjunction-class missions with long crewed durations and minimum energy trajectories to reduce total propellant requirements and total launch mass. However, in order to progressively reduce risk and gain experience in interplanetary mission operations, it may be desirable that initial human missions to Mars, whether to the surface or to Mars orbit, have shorter total crewed durations and minimal stay times at the destination. Opposition-class missions require larger total energy requirements relative to conjunction-class missions but offer the potential for much shorter mission durations, potentially reducing risk and overall systems performance requirements. This paper will present a detailed comparison of conjunction-class and opposition-class human missions to Mars vicinity with a focus on how such missions could be integrated into the initial phases of a Mars exploration campaign. The paper will present the results of a trade study that integrates trajectory/propellant analysis, element design, logistics and sparing analysis, and risk assessment to produce a comprehensive comparison of opposition and conjunction exploration mission constructs. Included in the trade study is an assessment of the risk to the crew and the trade offs between the mission duration and element, logistics, and spares mass. The analysis of the mission trade space was conducted using four simulation and analysis tools developed by NASA. Trajectory analyses for Mars destination missions were conducted using VISITOR (Versatile ImpulSive Interplanetary Trajectory OptimizeR), an in-house tool developed by NASA Langley Research Center. Architecture elements were evaluated using EXploration Architecture Model for IN-space and Earth-to-orbit (EXAMINE), a parametric modeling tool that generates exploration architectures through an integrated systems model. Logistics analysis was conducted using NASA's Human Exploration Logistics Model (HELM), and sparing allocation predictions were generated via the Exploration Maintainability Analysis Tool (EMAT), which is a probabilistic simulation engine that evaluates trades in spacecraft reliability and sparing requirements based on spacecraft system maintainability and reparability.

Mattfeld, Bryan↗