Search NASA⌕ Search

SEARCH · Search NASA

Results for “volume constraint”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

DESAP 1: A structural design program with stress and displacement constraints. Volume 1: Theoretical and user's manual

A finite element program is presented for computer-automated, minimum weight design of elastic structures with constraints on stresses (including local instability criteria) and displacements. Volume 1 of the report contains the theoretical and user's manual of the program. Sample problems and the listing of the program are included in Volumes 2 and 3. The element subroutines are organized so as to facilitate additions and changes by the user. As a result, a relatively minor programming effort would be required to make DESAP 1 into a special purpose program to handle the user's specific design requirements and failure criteria.

Kiusalaas, J.↗
NASA NTRS1977

DESAP 2: A structural design program with stress and buckling constraints. Volume 1: Theoretical and user's manual

DESAP 2 is described as a finite element program for computer-automated, minimum weight design of elastic structures with constraints on stresses (including local instability criteria) and buckling loads. No limits are placed on the number of load conditions for stress-constrained design, but only one of these load conditions can be chosen as the potential buckling load. A substantial portion of DESAP 2, particularly the analysis of the prebuckling state, is derived from the SOLID SAP finite element program. The stress-constrained design is based on the classical stress ratio method, which drives the design towards a fully stressed state. The constraints on the buckling load are handled by solving the appropriate optimality criterion by successive iterations. During each iteration, the element sizes determined by the stress ratio method are used as the minimum size constraints. The element subroutines are organized in a manner that permits the user to make additions and changes with a minimal programming effort. Consequently, DESAP 2 can readily be changed into a special-purpose program to handle the user's specific design requirements and failure criteria.

Kiusalaas, J.↗
NASA NTRS2016

Challenges of Designing a 13-Hz High-Load Vibration Isolation System with Tight Volume Constraints: Lessons Learned and Path Forward

This paper describes the design of a passive isolation system using D-struts (Registered TradeMark) to isolate an optical payload from aircraft-borne jitter with challenging stroke per volume requirements. It discusses the use of viscoelastic-coated D-struts® that meet the customer performance and outgassing specification, NASA-1124. The result was a relatively soft isolation system, (where the first mode was 13 Hz), with each individual strut capable of withstanding loads on the order of magnitude of 623 N (140 lbf), weighing less than 910 g (2 lbm), fitting in a volume 5.1 cm (2 inches) in diameter and 12-cm (4.7-inches) long and capable of performing up to 1000 Hz without nonlinearities.

Dearing, Stella↗
NASA NTRS2023

IMPACTing Medical System Design with a Risk Analysis Tool [“IMPACT” sur la Conception du Système Médical avec un Outil d'Analyse des Risques]

Background: Following the success of Artemis I, NASA is preparing for human extended duration missions. Ongoing efforts are focused on mitigating mission-related risks, including those affecting crew health and performance. Communication latency, logistics of resupply and time frame of medical evacuation are barriers to provision of healthcare for these missions, especially with respect to constraints in mass, volume, and crew training. An in-depth assessment of medical risks, capabilities and resources for a specific mission design is necessary to determine an optimal balance that maximizes likelihood of mission success. Overview: IMPACT (Informed Mission Planning via Analysis of Complex Tradespaces) is a dynamic tool designed to estimate medical risk and outcomes for a specific mission design. In its current iteration, a list of medical conditions selected based on likelihood of occurrence and/or consequence was linked to a set of clinical capabilities and resources necessary for diagnosis and management. A probabilistic risk analysis tool was then used to identify and estimate the likelihood and consequence of risks through the following outcome metrics: loss of crew life (inflight mortality due to medical conditions), need for medical evacuation (return to definitive care), and crew disability (task time affected based on how medical conditions influence the ability to perform specific exploration mission crew tasks). Finally, the model’s optimization algorithm provides recommendations for medical capabilities that maximize risk mitigation relative to mass and volume constraints. In the Spring of 2023, IMPACT was utilized to estimate outcome metrics for a design reference mission that would be representative of an extended duration Artemis mission. Notional data generated were then used to determine a recommended set of medical capabilities and resources relative to user-defined mass and volume constraints. A multidisciplinary team has also been updating IMPACT to strengthen the model’s fidelity. Figure 1 shows how updates to outcome metric inputs for the conditions resulted in different capability and resource allocation recommendations. Discussion: This presentation will discuss the IMPACT tool and share the latest data generated for a representative extended duration Artemis mission. Efforts to improve the fidelity of data generated by the model’s algorithm will also be discussed.

K A Shair↗
NASA NTRSDate not supplied

IMPACTing Medical System Design with a Risk Analysis Tool

Background: Following the success of Artemis I, NASA is preparing for human extended duration missions. Ongoing efforts are focused on mitigating mission-related risks, including those affecting crew health and performance. Communication latency, logistics of resupply and time frame of medical evacuation are barriers to provision of healthcare for these missions, especially with respect to constraints in mass, volume, and crew training. An in-depth assessment of medical risks, capabilities and resources for a specific mission design is necessary to determine an optimal balance that maximizes likelihood of mission success. Overview: IMPACT (Informed Mission Planning via Analysis of Complex Tradespaces) is a dynamic tool designed to estimate medical risk and outcomes for a specific mission design. In its current iteration, a list of medical conditions selected based on likelihood of occurrence and/or consequence was linked to a set of clinical capabilities and resources necessary for diagnosis and management. A probabilistic risk analysis tool was then used to identify and estimate the likelihood and consequence of risks through the following outcome metrics: loss of crew life (inflight mortality due to medical conditions), need for medical evacuation (return to definitive care), and crew disability (task time affected based on how medical conditions influence the ability to perform specific exploration mission crew tasks). Finally, the model’s optimization algorithm provides recommendations for medical capabilities that maximize risk mitigation relative to mass and volume constraints. In the Spring of 2023, IMPACT was utilized to estimate outcome metrics for a design reference mission that would be representative of an extended duration Artemis mission. Notional data generated were then used to determine a recommended set of medical capabilities and resources relative to user-defined mass and volume constraints. A multidisciplinary team has also been updating IMPACT to strengthen the model’s fidelity. Figure 1 shows how updates to outcome metric inputs for the conditions resulted in different capability and resource allocation recommendations. Discussion: This presentation will discuss the IMPACT tool and share the latest data generated for a representative extended duration Artemis mission. Efforts to improve the fidelity of data generated by the model’s algorithm will also be discussed.

K A Shair↗
NASA NTRS2022

New Rover Conops with High-Performance Onboard Computing: Give Up Raw Data to Reduce Ops Cost and Do More Science

A major portion of time during the tactical operation of Mars rovers is spent for selecting, prioritizing, and coordinating sciences and engineering activities such that they fit within resource constraints, including the downlink data volume, energy, and time. In particular, the downlink data volume constraint is getting particularly tighter in recent missions because modern instruments produce increasingly high data volume while the communication bandwidth is essentially bounded by the law of physics. Tactical operation would be substantially simplified, hence the operation cost could be reduced, if the data volume constraint is relaxed or even removed. In this abstract, we propose a new operation paradigm for achieving this goal. The key observation is that, both in science and engineering applications, the bit size of raw data is typically much greater than the volume of processed information that is needed for scientific or engineering analysis. For example, a full-resolution image from Mastcam-Z, the main science camera on Perseverance, is about 700 kB in volume and we downlinked 29,685 images up to Sol 243, totaling ~20 GB of data. But of course, scientists do not use every pixel of these images; what they really look for in the images are geological features, typically represented by specific geometric configurations or textures. An end product after processing hundreds of Mascam-Z images could be a single geological map summarizing the spatial distribution of the features. For another example, a 100-meter drive of Perseverance produces 7-12 MB of drive telemetry, which records every detail of the rover's motion at 8 Hz, including position, attitude, steering angles, encoder readings, motor currents and many other information. But what the ground engineers eventually pay attention to is the signs of anomaly, such as excessive motor currents or high slip; if a drive is nominal, the vast majority of this data is unused. What if, then, we process the raw data onboard and only downlink the processed data that is relevant to scientific or engineering analyses, such as a list of detected science features (with cropped images) or a list of potential signs of anomaly while driving? A major roadblock for such onboard, high-level information processing has been the onboard computational resource. RAD750, the main onboard computer of Perseverance, is obviously not sufficient for performing complex image or signal processing such as object detection, semantic segmentation, or anomaly detection. Interestingly, RAD750 is not the best processor that Perseverance has; Qualcomm's Snapdragon 801, a modern mobile processor, is on her Heli Base Station, a device for communicating with Mars Helicopter Ingenuity; also, Intel's Atom E3845 processors are on engineering cameras. In the reminder of this paper, we will introduce two particular uses cases of these high-performance co-processors (meaning auxiliary CPU, GPU, or other types of processors that are separate from the main processor that runs the main flight software) for lowering operation cost and accommodating more science activities for a given communication constraint.

Didier, A.↗
NASA NTRS2011

Generation of Parametric Equivalent-Area Targets for Design of Low-Boom Supersonic Concepts

A tool with an Excel visual interface is developed to generate equivalent-area (A(sub e)) targets that satisfy the volume constraints for a low-boom supersonic configuration. The new parametric Ae target explorer allows users to interactively study the tradeoffs between the aircraft volume constraints and the low-boom characteristics (e.g., loudness) of the ground signature. Moreover, numerical optimization can be used to generate the optimal A(sub e) target for given A(sub e) volume constraints. A case study is used to demonstrate how a generated low-boom Ae target can be matched by a supersonic configuration that includes a fuselage, wing, nacelle, pylon, aft pod, horizontal tail, and vertical tail. The low-boom configuration is verified by sonic-boom analysis with an off-body pressure distribution at three body lengths below the configuration

Li, Wu↗
NASA NTRS2020

Evaluation of Packing_3D Code for Design of Variable-Depth, Bent-Chamber Acoustic Liners

Increases in the bypass ratio for commercial aircraft engines have caused the broadband fan noise component to become dominant. As a result, there is a need to develop improved acoustic liners suitable for absorption of this fan noise over a wide frequency range, preferably up to at least two octaves. Variable depth liners with bent chambers and three-dimensional geometries present one way to achieve this goal, however, they can be difficult and time-consuming to design due to their complexity and volume constraints. A packing code, called Packing3D, has been developed that automatically designs the chamber configurations of such liners once the chamber dimensions and volume constraints are known. The code uses a randomized trial and error approach to place each chamber in a representation of the liner sample, then returns a colored diagram and sufficient information for the liner sample to be fabricated. For evaluation, the code is used to design four liner samples of varying levels of complexity. These samples are tested with and without a mesh facesheet in the NASA Langley Normal Incidence Tube, and the results are compared to predictions computed in COMSOL. The results indicate that the packing code is able to quickly design samples that are predictable, achieve the desired absorption spectrum, fit the given constraints, and are able to be built. This code is flexible, lends itself to optimization, and allows samples to be designed quickly, accurately, and efficiently.

Marinova, Miroslava M.↗
NASA NTRS2006

Planned Environmental Microbiology Aspects of Future Lunar and Mars Missions

With the establishment of the Constellation Program, NASA has initiated efforts designed similar to the Apollo Program to return to the moon and subsequently travel to Mars. Early lunar sorties will take 4 crewmembers to the moon for 4 to 7 days. Later missions will increase in duration up to 6 months as a lunar habitat is constructed. These missions and vehicle designs are the forerunners of further missions destined for human exploration of Mars. Throughout the planning and design process, lessons learned from the International Space Station (ISS) and past programs will be implemented toward future exploration goals. The standards and requirements for these missions will vary depending on life support systems, mission duration, crew activities, and payloads. From a microbiological perspective, preventative measures will remain the primary techniques to mitigate microbial risk. Thus, most of the effort will focus on stringent preflight monitoring requirements and engineering controls designed into the vehicle, such as HEPA air filters. Due to volume constraints in the CEV, in-flight monitoring will be limited for short-duration missions to the measurement of biocide concentration for water potability. Once long-duration habitation begins on the lunar surface, a more extensive environmental monitoring plan will be initiated. However, limited in-flight volume constraints and the inability to return samples to Earth will increase the need for crew capabilities in determining the nature of contamination problems and method of remediation. In addition, limited shelf life of current monitoring hardware consumables and limited capabilities to dispose of biohazardous trash will drive flight hardware toward non-culture based methodologies, such as hardware that rapidly distinguishes biotic versus abiotic surface contamination. As missions progress to Mars, environmental systems will depend heavily on regeneration of air and water and biological waste remediation and regeneration systems, increasing the need for environmental monitoring. Almost complete crew autonomy will be needed for assessment and remediation of contamination problems. Cabin capacity will be limited; thus, current methods of microbial monitoring will be inadequate. Future methodology must limit consumables, and these consumables must have a shelf life of over three years. In summary, missions to the moon and Mars will require a practical design that prudently uses available resources to mitigate microbial risk to the crew.

Ott, C. Mark↗
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 NTRS2011

The Use of the Integrated Medical Model for Forecasting and Mitigating Medical Risks for a Near-Earth Asteroid Mission

Introduction The Integrated Medical Model (IMM) is a decision support tool that is useful to space flight mission managers and medical system designers in assessing risks and optimizing medical systems. The IMM employs an evidence-based, probabilistic risk assessment (PRA) approach within the operational constraints of space flight. Methods Stochastic computational methods are used to forecast probability distributions of medical events, crew health metrics, medical resource utilization, and probability estimates of medical evacuation and loss of crew life. The IMM can also optimize medical kits within the constraints of mass and volume for specified missions. The IMM was used to forecast medical evacuation and loss of crew life probabilities, as well as crew health metrics for a near-earth asteroid (NEA) mission. An optimized medical kit for this mission was proposed based on the IMM simulation. Discussion The IMM can provide information to the space program regarding medical risks, including crew medical impairment, medical evacuation and loss of crew life. This information is valuable to mission managers and the space medicine community in assessing risk and developing mitigation strategies. Exploration missions such as NEA missions will have significant mass and volume constraints applied to the medical system. Appropriate allocation of medical resources will be critical to mission success. The IMM capability of optimizing medical systems based on specific crew and mission profiles will be advantageous to medical system designers. Conclusion The IMM is a decision support tool that can provide estimates of the impact of medical events on human space flight missions, such as crew impairment, evacuation, and loss of crew life. It can be used to support the development of mitigation strategies and to propose optimized medical systems for specified space flight missions. Learning Objectives The audience will learn how an evidence-based decision support tool can be used to help assess risk, develop mitigation strategies, and optimize medical systems for exploration space flight missions.

Kerstman, Eric↗
NASA NTRS2017

Optimization Routine for Generating Medical Kits for Spaceflight Using the Integrated Medical Model

The Integrated Medical Model (IMM) is a MATLAB model that provides probabilistic assessment of the medical risk associated with human spaceflight missions.Different simulations or profiles can be run in which input conditions regarding both mission characteristics and crew characteristics may vary. For each simulation, the IMM records the total medical events that occur and “treats” each event with resources drawn from import scripts. IMM outputs include Total Medical Events (TME), Crew Health Index (CHI), probability of Evacuation (pEVAC), and probability of Loss of Crew Life (pLOCL).The Crew Health Index is determined by the amount of quality time lost (QTL). Previously, an optimization code was implemented in order to efficiently generate medical kits. The kits were optimized to have the greatest benefit possible, given amass and/or volume constraint. A 6-crew, 14-day lunar mission was chosen for the simulation and run through the IMM for 100,000 trials. A built-in MATLAB solver, mixed-integer linear programming, was used for the optimization routine. Kits were generated in 10% increments ranging from 10%-100% of the benefit constraints. Conditions wheremass alone was minimized, volume alone was minimized, and where mass and volume were minimizedjointly were tested.

Medical Kit↗
NASA NTRS2014

A CubeSat Asteroid Mission: Design Study and Trade-Offs

There is considerable interest in expanding the applicability of cubesat spacecraft into lightweight, low cost missions beyond Low Earth Orbit. A conceptual design was done for a 6-U cubesat for a technology demonstration to demonstrate use of electric propulsion systems on a small satellite platform. The candidate objective was a mission to be launched on the SLS test launch EM-1 to visit a Near-Earth asteroid. Both asteroid fly-by and asteroid rendezvous missions were analyzed. Propulsion systems analyzed included cold-gas thruster systems, Hall and ion thrusters, incorporating either Xenon or Iodine propellant, and an electrospray thruster. The mission takes advantage of the ability of the SLS launch to place it into an initial trajectory of C3=0. Targeting asteroids that fly close to earth minimizes the propulsion required for fly-by/rendezvous. Due to mass constraints, high specific impulse is required, and volume constraints mean the propellant density was also of great importance to the ability to achieve the required deltaV. This improves the relative usefulness of the electrospray salt, with higher propellant density. In order to minimize high pressure tanks and volatiles, the salt electrospray and iodine ion propulsion systems were the optimum designs for the fly-by and rendezvous missions respectively combined with a thruster gimbal and wheel system For the candidate fly-by mission, with a mission deltaV of about 400 m/s, the mission objectives could be accomplished with a 800s electrospray propulsion system, incorporating a propellant-less cathode and a bellows salt tank. This propulsion system is planned for demonstration on 2015 LEO and 2016 GEO DARPA flights. For the rendezvous mission, at a ΔV of 2000 m/s, the mission could be accomplished with a 50W miniature ion propulsion system running iodine propellant. This propulsion system is not yet demonstrated in space. The conceptual design shows that an asteroid mission is possible using a cubesat platform with high-efficiency electric propulsion.

cubesat↗
NASA NTRS2016

Design and Development of NEA Scout Solar Sail Deployer Mechanism

The 6U (approximately 10cm x 20cm x 30cm) cubesat Near Earth Asteroid (NEA) Scout1, projected for launch in September 2018 aboard the maiden voyage of the Space Launch System (SLS), will utilize a solar sail as its main method of propulsion throughout its approximately 3 year mission to a Near Earth Asteroid (NEA). Due to the extreme volume constraints levied onto the mission, an acutely compact solar sail deployment mechanism has been designed to meet the volume and mass constraints, as well as provide enough propulsive solar sail area and quality in order to achieve mission success. The design of such a compact system required the development of approximately half a dozen prototypes in order to identify unforeseen problems, advance solutions, and build confidence in the final design product. This paper focuses on the obstacles of developing a solar sail deployment mechanism for such an application and the lessons learned from a thorough development process. The lessons presented will have significant applications beyond the NEA Scout mission, such as the development of other deployable boom mechanisms and uses for gossamer-thin films in space.

Sobey, Alexander R.↗