Results for “Scenario optimization” — Page 3

NASA NTRSDate not supplied

Human Mars Mission In-Space Transportation Sensitivity for Nuclear Electric / Chemical Hybrid Propulsion

NASA's Human Exploration and Operation Mission Directorate is continuing to study different concepts and options to field human Mars missions as part of NASA's Moon2Mars directive. In this study, an update to the Hybrid propulsion system was established with the introduction of nuclear electric propulsion system to replace the solar electric propulsion system in an effort to understand the potential impact of a shorter mission to Mars. For crewed missions to Mars, the transportation system sizing is highly dependent on the type of mission and the mission duration. An integrated trajectory analysis capability has been developed and updated to enable this investigation. Longer duration mission may utilize higher efficiency low thrust propulsion system more, but would require higher payload mass due to increase to crew logistics loading and habitation volume. Conversely, shorter duration mission may have lower payload mass, but will require significant increase to propulsion system performance and/or overall system mass. An overall integrated design trade space is defined in this paper to investigate the tradeoff between these scenarios to illuminate the optimality of the transportation system option from a mass perspective. The sensitivity analysis developed in this study will be crucial to understanding the Mars mission design trade space for crewed Mars missions, and will help inform design decisions and investment strategies.

Patrick R. Chai↗

NASA NTRS1993

Trajectory optimization for a National Launch System vehicle

A trajectory design process is presented for a proposed National Launch System (NLS) vehicle configuration. A software trajectory planner was developed to generate near optimal pitch plane trajectories for variable mission plans, variable launch site selections, and last minute wind conditions at the time of launch. In addition, the trajectory planner performs in-flight near optimal trajectory redesign in the event of an engine-out or unexpected wind dispersions. The trajectory planner iteratively simulates trial trajectories defined by variables corresponding to a parameterized trajectory shape. The trajectory planner optimizes these trajectory parameters according to the fuel used to realize the trajectories. For prelaunch scenarios, the trajectory planner generated near optimal trajectories of consistent fuel performance irrespective of the winds encountered at the launch site. In-flight trajectory redesigns were also shown to be effective in fulfilling the mission plan and preserving the structural integrity of the vehicle. The in-flight redesign results indicate that closed-loop guidance in the early stages of ascent is highly effective in accommodating engine failures or wind dispersions. All trajectory designs were verified using a 6DOF simulation with flight controllers.

Chen, Eugene S.↗

NASA NTRSDate not supplied

Determining Optimal Asset Location for Rapid and Efficient Wildfire Suppression: A Simulation-Based Approach

The impact of wildfire incidents has been growing in recent years, posing a serious threat to communities at the urban-wildland interface. To address this problem, there have been growing calls to use UAVs to increase the capacity of responsible agencies to quickly and effectively suppress fires and to reduce risks associated with firefighting. One of the opportunities associated with UAVs is the ability to rapidly and autonomously operate from limited-access air bases where fires are expected to burn. This study provides an approach to determine where these air bases should be placed in order to most rapidly extinguish fires, given provided fuel distributions. This approach uses an integrated simulation of fire propagation and UAV-based suppression actions to determine how much of a given environment was burned over a range of scenarios. It then uses an optimization method to explore the space and determine the location with the least burned area. Results show the approach to efficiently and effectively provide optimal bases for single-base placements over a range of scenarios, though future work is required to adequately calibrate the model and study how it can be used in multiple-base placement problems.

Daniel Hulse↗

NASA NTRSDate not supplied

Determining Optimal Asset Location for Rapid and Efficient Wildfire Suppression: A Simulation-Based Approach

The impact of wildfire incidents has been growing in recent years, posing a serious threat to communities at the urban-wildland interface. To address this problem, there have been growing calls to use UAVs to increase the capacity of responsible agencies to quickly and effectively suppress fires and to reduce risks associated with firefighting. One of the opportunities associated with UAVs is the ability to rapidly and autonomously operate from limited-access air bases where fires are expected to burn. This study provides an approach to determine where these air bases should be placed in order to most rapidly extinguish fires, given provided fuel distributions. This approach uses an integrated simulation of fire propagation and UAV-based suppression actions to determine how much of a given environment was burned over a range of scenarios. It then uses an optimization method to explore the space and determine the location with the least burned area. Results show the approach to efficiently and effectively provide optimal bases for single-base placements over a range of scenarios, though future work is required to adequately calibrate the model and study how it can be used in multiple-base placement problems.

Daniel Hulse↗

NASA NTRS2017

Integrating Growth Stage Deficit Irrigation into a Process Based Crop Model

Current rates of agricultural water use are unsustainable in many regions, creating an urgent need to identify improved irrigation strategies for water limited areas. Crop models can be used to quantify plant water requirements, predict the impact of water shortages on yield, and calculate water productivity (WP) to link water availability and crop yields for economic analyses. Many simulations of crop growth and development, especially in regional and global assessments, rely on automatic irrigation algorithms to estimate irrigation dates and amounts. However, these algorithms are not well suited for water limited regions because they have simplistic irrigation rules, such as a single soil-moisture based threshold, and assume unlimited water. To address this constraint, a new modeling framework to simulate agricultural production in water limited areas was developed. The framework consists of a new automatic irrigation algorithm for the simulation of growth stage based deficit irrigation under limited seasonal water availability; and optimization of growth stage specific parameters. The new automatic irrigation algorithm was used to simulate maize and soybean in Gainesville, Florida, and first used to evaluate the sensitivity of maize and soybean simulations to irrigation at different growth stages and then to test the hypothesis that water productivity calculated using simplistic irrigation rules underestimates WP. In the first experiment, the effect of irrigating at specific growth stages on yield and irrigation water use efficiency (IWUE) in maize and soybean was evaluated. In the reproductive stages, IWUE tended to be higher than in the vegetative stages (e.g. IWUE was 18% higher than the well watered treatment when irrigating only during R3 in soybean), and when rainfall events were less frequent. In the second experiment, water productivity (WP) was significantly greater with optimized irrigation schedules compared to non-optimized irrigation schedules in water restricted scenarios. For example, the mean WP across 38 years of maize production was 1.1 kg/cu m for non-optimized irrigation schedules with 50 mm of seasonal available water and 2.1 kg/cu m optimized ion schedules, a 91% improvement in WP with optimized irrigation schedules. The framework described in this work could be used to estimate WP for regional to global assessments, as well as derive location specific irrigation guidance.

crop model↗

NASA NTRSDate not supplied

Optimizing CO2 Washout in the Exploration Extravehicular Mobility Unit

CO2 Washout refers to the suit’s ability to remove exhaled metabolic waste gases from the helmet before the crewmember’s next consecutive inhale. Efficient removal of such waste gases is paramount as it prevents crewmember fatigue as well as hypoxia. A variety of hardware and conditions inside the suit contribute to the efficiency at which CO2 washout occurs including (but not limited to) the shape of the helmet bubble, crewmember head position, breathing type and metabolic rate, the configuration of the oxygen vent inside the helmet, etc. While designing the oxygen vent inside the helmet of the Extravehicular Mobility Unit (xEMU) both nominal and contingency scenarios were considered in order to optimize CO2 washout. During nominal Extravehicular Activity (EVA), the pressure gradient created by the vent loop inlets located in the arms and legs of the Pressure Garment Subsystem (PGS) aids in washout by pulling the metabolic waste out of the helmet. However, in the event that a contingency scenario occurs, where the flow of oxygen to the crewmember, or the removal of metabolic waste is disrupted, the primary oxygen regulator fails open and removal of waste is no longer performed by the vent loop, but rather by the Low Flow Purge Valve (LFPV) located in the helmet. The paper to follow will provide an overview of the analysis, design, and testing performed to optimize washout for both nominal and contingency scenarios for the most current design iteration of the xEMU.

Margot Steely↗

NASA NTRS2001

Fast Quaternion Attitude Estimation from Two Vector Measurements

Many spacecraft attitude determination methods use exactly two vector measurements. The two vectors are typically the unit vector to the Sun and the Earth's magnetic field vector for coarse "sun-mag" attitude determination or unit vectors to two stars tracked by two star trackers for fine attitude determination. Existing closed-form attitude estimates based on Wahba's optimality criterion for two arbitrarily weighted observations are somewhat slow to evaluate. This paper presents two new fast quaternion attitude estimation algorithms using two vector observations, one optimal and one suboptimal. The suboptimal method gives the same estimate as the TRIAD algorithm, at reduced computational cost. Simulations show that the TRIAD estimate is almost as accurate as the optimal estimate in representative test scenarios.

Markley, F. Landis↗

NASA NTRS2009

Using Covariance Analysis to Assess Pointing Performance

A Pointing Covariance Analysis Tool (PCAT) has been developed for evaluating the expected performance of the pointing control system for NASA s Space Interferometry Mission (SIM). The SIM pointing control system is very complex, consisting of multiple feedback and feedforward loops, and operating with multiple latencies and data rates. The SIM pointing problem is particularly challenging due to the effects of thermomechanical drifts in concert with the long camera exposures needed to image dim stars. Other pointing error sources include sensor noises, mechanical vibrations, and errors in the feedforward signals. PCAT models the effects of finite camera exposures and all other error sources using linear system elements. This allows the pointing analysis to be performed using linear covariance analysis. PCAT propagates the error covariance using a Lyapunov equation associated with time-varying discrete and continuous-time system matrices. Unlike Monte Carlo analysis, which could involve thousands of computational runs for a single assessment, the PCAT analysis performs the same assessment in a single run. This capability facilitates the analysis of parametric studies, design trades, and "what-if" scenarios for quickly evaluating and optimizing the control system architecture and design.

Bayard, David↗

NASA NTRS2016

Commercial Application of In-Space Assembly

In-Space assembly (ISA) expands the opportunities for cost effective emplacement of systems in space. Currently, spacecraft are launched into space and deploy into their operational configuration through a carefully choreographed sequence of operations. The deployment operation dictates the arrangement of the primary systems on the spacecraft, limiting the ability to take full advantage of launch vehicles volume and mass capability. ISA enables vastly different spacecraft architectures and emplacement scenarios to be achieved, including optimal launch configurations ranging from single launch and assembly to on-orbit aggregation of multiple launches at different orbital locations and times. The spacecraft can be visited at different orbital locations and times to effect expansion and maintenance of an operational capability. To date, the primary application of ISA has been in large programs funded by government organizations, such as the International Space Station. Recently, Space Systems Loral (SSL) led a study funded by the Defense Advanced Research Projects Agency (DARPA), called Dragonfly, to investigate the commercial applicability and economic advantages of ISA. In the study, it was shown that ISA enables SSL to double the capability of a commercial satellite system by taking advantage of alternate packaging approaches for the reflectors. The study included an ultra-light-weight robotic system, derived from Mars manipulator designs, to complete assembly of portions of the antenna system using a tool derived from DARPA orbital express and National Aeronautics and Space Administration (NASA) automated structural assembly experience. The mechanical connector that enables robotic ISA takes advantage of decades of development by NASA from the 1970's to 1980's during the Space Station Freedom program, the precursor to the ISS. The mechanical connector was originally designed for rapid astronaut assembly while also providing a high quality structural connection with linear load deflection response. The paper will discuss the business case for ISA, the general approach taken to exploit on-orbit assembly in the GEO communication satellite market, and the concept of operations associated with the ISA approach, thus laying the foundation for ISA to become an accepted operational approach for commercial in-space operations.

Lymer, John↗

NASA NTRSDate not supplied

Design of a Wind Tunnel Balance using Topology Optimization Considering Multifunctional Stress Performance

This paper proposes a new topology optimization formulation for multi-functional performance of a compliant sensor structure–a wind tunnel balance. Compliant mechanism design is one of the main applications of topology optimization and plenty of successful design studies have been reported. However, design practicability is still questionable when stress concentration is critical due to complex/combined loads, especially at compliant hinge joints. In this paper, we formulate a new topology optimization formulation considering multiple loading scenarios in a compliant sensor structure design. Two separate constraints,one related to sensor performance and the other focused on structural safety in terms of maximum von Mises stress, are included in the design formulation. This formulation is to achieve excellent sensitivity of an applied axial load while maintaining structure safety with a combined general load applied which is one order higher than the axial load. This challenging problem is solved using a well-known SIMP approach with the relaxation and projection methods.

Myung Kyun Sung↗

NASA NTRS2008

Lunar Outpost Life Support Trade Studies

Engineering trade-off studies of life support system architecture and technology options were conducted for potential lunar surface mission scenarios within NASA's Constellation Program. The scenarios investigated are based largely on results of the NASA Lunar Architecture Team (LAT) Phase II study. In particular, the possibility of Hosted Sortie missions, the high cost of power during eclipse periods, and the potential to reduce life support consumables through scavenging, in-situ resources, and alternative EVA technologies were all examined. These trade studies were performed within the Systems Integration, Modeling and Analysis (SIMA) element of NASA's Exploration Life Support (ELS) technology development project. The tools and methodology used in the study are described briefly, followed by a discussion of mission scenarios, life support technology options and results presented in terms of equivalent system mass for various regenerative life support technologies and architectures. Three classes of repeated or extended lunar surface missions were investigated in this study along with several life support resource scenarios for each mission class. Individual mission durations of 14 days, 90 days and 180 days were considered with 10 missions assumed for each at a rate of 2 missions per year. The 14-day missions represent a class of Hosted Sortie missions where a pre-deployed and potentially mobile habitat provides life support for multiple crews at one or more locations. The 90-day and 180-day missions represent lunar outpost expeditions with a larger fixed habitat. The 180-day missions assume continuous human presence and must provide life support through eclipse periods of up to 122 hours while the 90-day missions are planned for best-case periods of nearly continuous sunlight. This paper investigates system optimization within the assumptions of each scenario and addresses how the scenario selected drives the life support system to different designs. Subsequently, these analysis results can be used to determine which technologies may be good choices throughout a broad range of architectures.

Lange, Kevin E.↗

NASA NTRS2008

A Comparison of Probabilistic and Deterministic Campaign Analysis for Human Space Exploration

Human space exploration is by its very nature an uncertain endeavor. Vehicle reliability, technology development risk, budgetary uncertainty, and launch uncertainty all contribute to stochasticity in an exploration scenario. However, traditional strategic analysis has been done in a deterministic manner, analyzing and optimizing the performance of a series of planned missions. History has shown that exploration scenarios rarely follow such a planned schedule. This paper describes a methodology to integrate deterministic and probabilistic analysis of scenarios in support of human space exploration. Probabilistic strategic analysis is used to simulate "possible" scenario outcomes, based upon the likelihood of occurrence of certain events and a set of pre-determined contingency rules. The results of the probabilistic analysis are compared to the nominal results from the deterministic analysis to evaluate the robustness of the scenario to adverse events and to test and optimize contingency planning.

Merrill, R. Gabe↗

NASA NTRS2014

Optimizing Medical Kits for Spaceflight

The Integrated Medical Model (IMM) is a probabilistic model that estimates medical event occurrences and mission outcomes for different mission profiles. IMM simulation outcomes describing the impact of medical events on the mission may be used to optimize the allocation of resources in medical kits. Efficient allocation of medical resources, subject to certain mass and volume constraints, is crucial to ensuring the best outcomes of in-flight medical events. We implement a new approach to this medical kit optimization problem. METHODS We frame medical kit optimization as a modified knapsack problem and implement an algorithm utilizing a dynamic programming technique. Using this algorithm, optimized medical kits were generated for 3 different mission scenarios with the goal of minimizing the probability of evacuation and maximizing the Crew Health Index (CHI) for each mission subject to mass and volume constraints. Simulation outcomes using these kits were also compared to outcomes using kits optimized..RESULTS The optimized medical kits generated by the algorithm described here resulted in predicted mission outcomes more closely approached the unlimited-resource scenario for Crew Health Index (CHI) than the implementation in under all optimization priorities. Furthermore, the approach described here improves upon in reducing evacuation when the optimization priority is minimizing the probability of evacuation. CONCLUSIONS This algorithm provides an efficient, effective means to objectively allocate medical resources for spaceflight missions using the Integrated Medical Model.

Optimization↗

NASA NTRS1986

Conceptual design studies for surface infrastructure

The utimate design of a manned Mars base will be the result of considerable engineering analysis and many trade studies to optimize the configuration. Many options and scenarios are available and all need to be considered at this time. Initial base elements, two base configuration concepts, internal space architectural concerns, and two base set-up scenarios are discussed. There are many variables as well as many unknowns to be reckoned with before people set foot on the red planet.

Ann L Bufkin↗

NASA NTRS1997

A Functional Simulator of Spacecraft Resources

The SPAcecraft SIMulator (SPASIM) simulates the functions and resources of a spacecraft to quickly perform Phase A trade-off analyses and uncover any operational bottlenecks during any part of the mission. Failure modes and operational contingencies can be evaluated allowing optimization for a range of mission scenarios. The payloads and subsystems are simulated, using a hierarchy of graphical models, in terms of how their functions affect resources such as propellant, power, and data. Any of the inputs and outputs of the payloads and subsystems can be plotted during the simulation. Most trade-off analyses, including those that compare current versus advanced technology, can be performed by changing values in the parameter menus. However, when a component is replaced by one with a different functional architecture, its graphical model can also be modified or replaced by drawing from a component library. SPASIM has been validated using several spacecraft designs which were at least at the Critical Design Review level. The user and programmer guide, including figures, is available on line as a hyper text document. This is an easy-to-use and expand tool which is based on MATLAB and SIMULINK. It runs on SGI workstations and PCs under Windows 95 or NT.

Liceaga, Carlos A.↗

NASA NTRS2005

Managing Space Radiation Risks On Lunar and Mars Missions: Risk Assessment and Mitigation

Radiation-induced health risks are a primary concern for human exploration outside the Earth's magnetosphere, and require improved approaches to risk estimation and tools for mitigation including shielding and biological countermeasures. Solar proton events are the major concern for short-term lunar missions (<60 d), and for long-term missions (>60 d) such as Mars exploration, the exposures to the high energy and charge (HZE) ions that make-up the galactic cosmic rays are the major concern. Health risks from radiation exposure are chronic risks including carcinogenesis and degenerative tissue risks, central nervous system effects, and acute risk such as radiation sickness or early lethality. The current estimate is that a more than four-fold uncertainty exists in the projection of lifetime mortality risk from cosmic rays, which severely limits analysis of possible benefits of shielding or biological countermeasure designs. Uncertainties in risk projections are largely due to insufficient knowledge of HZE ion radiobiology, which has led NASA to develop a unique probabilistic approach to radiation protection. We review NASA's approach to radiation risk assessment including its impact on astronaut dose limits and application of the ALARA (As Low as Reasonably Achievable) principle. The recently opened NASA Space Radiation Laboratory (NSRL) provides the capability to simulate the cosmic rays in controlled ground-based experiments with biological and shielding models. We discuss how research at NSRL will lead to reductions in the uncertainties in risk projection models. In developing mission designs, the reduction of health risks and mission constraints including costs are competing concerns that need to be addressed through optimization procedures. Mitigating the risks from space radiation is a multi-factorial problem involving individual factors (age, gender, genetic makeup, and exposure history), operational factors (planetary destination, mission length, and period in the solar cycle), and shielding characteristics (materials, mass, and topology). We review optimization metrics for radiation protection including scenarios that integrate biophysics models of radiation risks, operational variables, and shielding design tools needed to assess exploration mission designs. We discuss the application of a crosscutting metric, based on probabilistic risk assessment, to lunar and Mars mission trade studies including the assessment of multi-factorial problems and the potential benefits of new radiation health research strategies or mitigation technologies.

Cucinotta, F. A.↗

NASA NTRS2005

Managing Space Radiation Risks on Lunar and Mars Missions: Risk Assessment and Mitigation

Radiation-induced health risks are a primary concern for human exploration outside the Earth's magnetosphere, and require improved approaches to risk estimation and tools for mitigation including shielding and biological countermeasures. Solar proton events are the major concern for short-term lunar missions (<60 d), and for long-term missions (>60 d) such as Mars exploration, the exposures to the high energy and charge (HZE) ions that make-up the galactic cosmic rays are the major concern. Health risks from radiation exposure are chronic risks including carcinogenesis and degenerative tissue risks, central nervous system effects, and acute risk such as radiation sickness or early lethality. The current estimate is that a more than four-fold uncertainty exists in the projection of lifetime mortality risk from cosmic rays, which severely limits analysis of possible benefits of shielding or biological countermeasure designs. Uncertainties in risk projections are largely due to insufficient knowledge of HZE ion radiobiology, which has led NASA to develop a unique probabilistic approach to radiation protection. We review NASA's approach to radiation risk assessment including its impact on astronaut dose limits and application of the ALARA (As Low as Reasonably Achievable) principle. The recently opened NASA Space Radiation Laboratory (NSRL) provides the capability to simulate the cosmic rays in controlled ground-based experiments with biological and shielding models. We discuss how research at NSRL will lead to reductions in the uncertainties in risk projection models. In developing mission designs, the reduction of health risks and mission constraints including costs are competing concerns that need to be addressed through optimization procedures. Mitigating the risks from space radiation is a multi-factorial problem involving individual factors (age, gender, genetic makeup, and exposure history), operational factors (planetary destination, mission length, and period in the solar cycle), and shielding characteristics (materials, mass, and topology). We review optimization metrics for radiation protection including scenarios that integrate biophysics models of radiation risks, operational variables, and shielding design tools needed to assess exploration mission designs. We discuss the application of a crosscutting metric, based on probabilistic risk assessment, to lunar and Mars mission trade studies including the assessment of multi-factorial problems and the potential benefits of new radiation health research strategies or mitigation technologies.

Cucinotta, F. A.↗

NASA NTRS2006

Managing Space Radiation Risks on Lunar and Mars Missions: Risk Assessment and Mitigation

Radiation-induced health risks are a primary concern for human exploration outside the Earth's magnetosphere, and require improved approaches to risk estimation and tools for mitigation including shielding and biological countermeasures. Solar proton events are the major concern for short-term lunar missions (<60 d), and for long-term missions (>60 d) such as Mars exploration, the exposures to the high energy and charge (HZE) ions that make-up the galactic cosmic rays are the major concern. Health risks from radiation exposure are chronic risks including carcinogenesis and degenerative tissue risks, central nervous system effects, and acute risk such as radiation sickness or early lethality. The current estimate is that a more than four-fold uncertainty exists in the projection of lifetime mortality risk from cosmic rays, which severely limits analysis of possible benefits of shielding or biological countermeasure designs. Uncertainties in risk projections are largely due to insufficient knowledge of HZE ion radiobiology, which has led NASA to develop a unique probabilistic approach to radiation protection. We review NASA's approach to radiation risk assessment including its impact on astronaut dose limits and application of the ALARA (As Low as Reasonably Achievable) principle. The recently opened NASA Space Radiation Laboratory (NSRL) provides the capability to simulate the cosmic rays in controlled ground-based experiments with biological and shielding models. We discuss how research at NSRL will lead to reductions in the uncertainties in risk projection models. In developing mission designs, the reduction of health risks and mission constraints including costs are competing concerns that need to be addressed through optimization procedures. Mitigating the risks from space radiation is a multi-factorial problem involving individual factors (age, gender, genetic makeup, and exposure history), operational factors (planetary destination, mission length, and period in the solar cycle), and shielding characteristics (materials, mass, and topology). We review optimization metrics for radiation protection including scenarios that integrate biophysics models of radiation risks, operational variables, and shielding design tools needed to assess exploration mission designs. We discuss the application of a crosscutting metric, based on probabilistic risk assessment, to lunar and Mars mission trade studies including the assessment of multi-factorial problems and the potential benefits of new radiation health research strategies or mitigation technologies.

Cucinotta, F. A.↗