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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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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

On the accuracy of pixel relaxation labeling

An analysis of pixel labeling by probabilistic relaxation techniques is presented to demonstrate that these labeling procedures degenerate to weighted averages in the vicinity of fixed points. A consequence of this is that undesired label conversions can occur, leading to a deterioration of labeling accuracy at a stage after an improvement has already been achieved. Means for overcoming the accuracy deterioration are suggested and used as the basis for a possible design strategy for using probabilistic relaxation procedures. The results obtained are illustrated using simple data sets in which labeling on individual pixels can be examined and also using Landsat imagery to show application to data typical of that encountered in remote sensing applications.

Richards, J. A.↗
NASA NTRS1985

Probabilistic Finite Element: Variational Theory

The goal of this research is to provide techniques which are cost-effective and enable the engineer to evaluate the effect of uncertainties in complex finite element models. Embedding the probabilistic aspects in a variational formulation is a natural approach. In addition, a variational approach to probabilistic finite elements enables it to be incorporated within standard finite element methodologies. Therefore, once the procedures are developed, they can easily be adapted to existing general purpose programs. Furthermore, the variational basis for these methods enables them to be adapted to a wide variety of structural elements and to provide a consistent basis for incorporating probabilistic features in many aspects of the structural problem. Tasks concluded include the theoretical development of probabilistic variational equations for structural dynamics, the development of efficient numerical algorithms for probabilistic sensitivity displacement and stress analysis, and integration of methodologies into a pilot computer code.

Belytschko, T.↗
NASA NTRS1990

Analysis of success probability/cost trades for small landers in a Mars network

The premise to be tested in this analysis is whether cost economics may accrue by delivering more landers designed to lower reliability of operation (compared to fewer landers of higher reliability) to obtain a desired probability of achieving a given number of lander successes. Generally, the application in mind is a network of penetrators, although the analysis may apply as well to other small lander concepts or even to simple rovers. The method of analysis is based on a probabilistic model of lander success and a related probabilistic model of project cost including the lander, spacecraft carrier, and integration, but not launch or operations costs. Quantitative results are obtained in a normalized and parametric fashion. Sensitivity to the assumed model parameters is also examined.

Friedlander, Alan L.↗
NASA NTRS2009

Reliability-Based Design Optimization of a Composite Airframe Component

A stochastic design optimization methodology (SDO) has been developed to design components of an airframe structure that can be made of metallic and composite materials. The design is obtained as a function of the risk level, or reliability, p. The design method treats uncertainties in load, strength, and material properties as distribution functions, which are defined with mean values and standard deviations. A design constraint or a failure mode is specified as a function of reliability p. Solution to stochastic optimization yields the weight of a structure as a function of reliability p. Optimum weight versus reliability p traced out an inverted-S-shaped graph. The center of the inverted-S graph corresponded to 50 percent (p = 0.5) probability of success. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure that corresponds to unity for reliability p (or p = 1). Weight can be reduced to a small value for the most failure-prone design with a reliability that approaches zero (p = 0). Reliability can be changed for different components of an airframe structure. For example, the landing gear can be designed for a very high reliability, whereas it can be reduced to a small extent for a raked wingtip. The SDO capability is obtained by combining three codes: (1) The MSC/Nastran code was the deterministic analysis tool, (2) The fast probabilistic integrator, or the FPI module of the NESSUS software, was the probabilistic calculator, and (3) NASA Glenn Research Center s optimization testbed CometBoards became the optimizer. The SDO capability requires a finite element structural model, a material model, a load model, and a design model. The stochastic optimization concept is illustrated considering an academic example and a real-life raked wingtip structure of the Boeing 767-400 extended range airliner made of metallic and composite materials.

Patnaik, Surya N.↗
NASA NTRS2008

Modeling the Risk of Fire/Explosion Due to Oxidizer/Fuel Leaks in the Ares I Interstage

A significant flight hazard associated with liquid propellants, such as those used in the upper stage of NASA's new Ares I launch vehicle, is the possibility of leakage of hazardous fluids resulting in a catastrophic fire/explosion. The enclosed and vented interstage of the Ares I contains numerous oxidizer and fuel supply lines as well as ignition sources. The potential for fire/explosion due to leaks during ascent depends on the relative concentrations of hazardous and inert fluids within the interstage along with other variables such as pressure, temperature, leak rates, and fluid outgasing rates. This analysis improves on previous NASA Probabilistic Risk Assessment (PRA) estimates of the probability of deflagration, in which many of the variables pertinent to the problem were not explicitly modeled as a function of time. This paper presents the modeling methodology developed to analyze these risks.

Ring, Robert W.↗
NASA NTRS2014

Preliminary Structural Sensitivity Study of Hypersonic Inflatable Aerodynamic Decelerator Using Probabilistic Methods

Acceptance of new spacecraft structural architectures and concepts requires validated design methods to minimize the expense involved with technology validation via flighttesting. This paper explores the implementation of probabilistic methods in the sensitivity analysis of the structural response of a Hypersonic Inflatable Aerodynamic Decelerator (HIAD). HIAD architectures are attractive for spacecraft deceleration because they are lightweight, store compactly, and utilize the atmosphere to decelerate a spacecraft during re-entry. However, designers are hesitant to include these inflatable approaches for large payloads or spacecraft because of the lack of flight validation. In the example presented here, the structural parameters of an existing HIAD model have been varied to illustrate the design approach utilizing uncertainty-based methods. Surrogate models have been used to reduce computational expense several orders of magnitude. The suitability of the design is based on assessing variation in the resulting cone angle. The acceptable cone angle variation would rely on the aerodynamic requirements.

Lyle, Karen H.↗
NASA NTRS2016

Pharmaceuticals Exposed to the Space Environment: Problems and Prospects

The NASA Human Research Program (HRP) Health Countermeasures Element maintains ongoing efforts to inform detailed risks, gaps, and further questions associated with the use of pharmaceuticals in space. Most recently, the Pharmacology Risk Report, released in 2010, illustrates the problems associated with maintaining pharmaceutical efficacy. Since the report, one key publication includes evaluation of pharmaceutical products stored on the International Space Station (ISS). This study shows that selected pharmaceuticals on ISS have a shorter shelf-life in space than corresponding terrestrial controls. The HRP Human Research Roadmap for planetary exploration identifies the risk of ineffective or toxic medications due to long-term storage during missions to Mars. The roadmap also identifies the need to understand and predict how pharmaceuticals will behave when exposed to radiation for long durations. Terrestrial studies of returned samples offer a start for predictive modeling. This paper shows that pharmaceuticals returned to Earth for post-flight analyses are amenable to a Weibull distribution analysis in order to support probabilistic risk assessment modeling. The paper also considers the prospect of passive payloads of key pharmaceuticals on sample return missions outside of Earth's magnetic field to gather additional statistics. Ongoing work in radiation chemistry suggests possible mitigation strategies where future work could be done at cryogenic temperatures to explore methods for preserving the strength of pharmaceuticals in the space radiation environment, perhaps one day leading to an architecture where pharmaceuticals are cached on the Martian surface and preserved cryogenically.

pharmacology↗
NASA NTRSDate not supplied

Cost and Throughput Analysis for the NASA Ames Arc Jet Modernization Program

NASA Ames Center is currently evaluating alternatives to modernize the Arc Jet Complex, a critical part of testing for NASA’s planetary missions. NASA’s Arc Jet Complex facilities “are used to simulate the aerothermodynamic heating that a spacecraft endures throughout hypersonic atmospheric entry, and to test candidate thermal protection system (TPS) materials and systems. “Because planetary mission schedules often have tight windows due to planetary alignment constraints, a small increase in schedule could result in a two-year delay. Such a delay could increase the cost of a $1billionmissionbyhundreds of millions of dollars due to project personnel pay and clean room storage. To avoid these costs, the authors support NASA Ames in evaluating return on investment (ROI) and effectiveness of alternatives for modernizing the complex. The first input into the ROI is the deconstruction and construction cost estimates, which are developed using independent research on highly specialized subsystems, vendor quotes, and Unified Facilities Criteria (UFC), depending on the facility and work package. One of the measures of effectiveness is throughput analysis of the test bays, as a main goal of the modernization is to increase the number of possible test runs per year. This analysis is conducted via a probabilistic simulation and accounts for a variety of stochastic factors that influence the sequence of test runs, such as the facility availability; test complexity; the need to pause to assess test results; test failure; and the possibility of a system failure. The methodologies for both these analyses are discussed, along with the challenges presented due to the unique nature of the highly specialized test equipment.

Jennifer Scheel↗
NASA NTRSDate not supplied

Baseline Medical System Translation for the Impact Medical Database

NASA has developed a new evidence-based data-driven probabilistic risk assessment and tradespace analysis tool as a successor to the Integrated Medical Model (IMM). This updated decision support tool is known as IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces). Whereas IMM focuses on the resources and risks associated with International Space Station (ISS) and Low Earth Orbit (LEO) missions, IMPACT estimates the frequency and consequences of medical conditions that might arise during exploration missions. One of the services offered by IMM is a series of generic or baseline medical systems associated with typical mission types or DRMs (Design Reference Missions), such that requestors may prioritize questions pertaining to the mission itself over the medical supplies indicated by the model outputs for that DRM. In a mission focused request, the appropriate baseline medical system is used in place of a prepared or optimized medical kit. In preparation, an effort was undertaken to create baseline systems of medical resources within IMPACT suitable for typical DRMs. Using an existing baseline medical system within IMM’s Integrated Medical Evidence Database (iMED) as a starting point, the resources found within the medical kit were compared to and substituted for equivalent resources available within the IMPACT MD (Medical Database). In consultation with clinicians with knowledge of IMPACT’s MD, each resource was matched as closely as possible to a similarly purposed resource in IMPACT, seeking to preserve the treatment capabilities and procedures offered by the IMM medical system while reconciling the differences in modeled resources and medical conditions between the models. To demonstrate the efficacy of this work, a prototype ISS medical system in IMPACT was translated from the baseline used in the IMM. The appropriate medical system was then run through its associated medical model to compare and validate the resultant risks and risk mitigation provided by each baseline ISS medical kit.

S Schwartz↗
NASA NTRSDate not supplied

LOFTID Aeroshell Thermal Response Uncertainty Analysis Utilizing the End-to-End Monte Carlo Approach

A probabilistic thermal margin process has been performed to design the flexible thermal protection system (FTPS) and select entry trajectory constraints given an acceptable risk level for the Low-Earth Orbit Flight Test of and Inflatable Decelerator (LOFTID) project. Uncertainties exist in atmospheric entry aeroheating environments and the predicted thermal response of thermal protection system (TPS) material. Entry vehicle TPS is often over-sized to mitigate uncertainty by combining conservative bounding scenarios together. The probabilistic thermal margin process allows engineers to make informed aeroshell design, flight design, and FTPS performance risk trades while preventing excessive FTPS margin from being applied. This paper describes the uncertainty analysis methodology used to carry out a probabilistic thermal margin process used for LOFTID’s aeroshell and explains how the calculated probability of exceeding flight allowable temperatures is used to design the FTPS and establish nominal flight design constraints. This probabilistic thermal margin process had never been applied to entry, decent, and landing design for a flown entry vehicle and it is one of the LOFTID project’s goals to demonstrate its merits.

Steven Andrew Tobin↗
NASA NTRS2005

Monte Carlo Simulation of Markov, Semi-Markov, and Generalized Semi- Markov Processes in Probabilistic Risk Assessment

A standard tool of reliability analysis used at NASA-JSC is the event tree. An event tree is simply a probability tree, with the probabilities determining the next step through the tree specified at each node. The nodal probabilities are determined by a reliability study of the physical system at work for a particular node. The reliability study performed at a node is typically referred to as a fault tree analysis, with the potential of a fault tree existing.for each node on the event tree. When examining an event tree it is obvious why the event tree/fault tree approach has been adopted. Typical event trees are quite complex in nature, and the event tree/fault tree approach provides a systematic and organized approach to reliability analysis. The purpose of this study was two fold. Firstly, we wanted to explore the possibility that a semi-Markov process can create dependencies between sojourn times (the times it takes to transition from one state to the next) that can decrease the uncertainty when estimating time to failures. Using a generalized semi-Markov model, we studied a four element reliability model and were able to demonstrate such sojourn time dependencies. Secondly, we wanted to study the use of semi-Markov processes to introduce a time variable into the event tree diagrams that are commonly developed in PRA (Probabilistic Risk Assessment) analyses. Event tree end states which change with time are more representative of failure scenarios than are the usual static probability-derived end states.

English, Thomas↗
NASA NTRS1995

Probabilistic risk assessment of the Space Shuttle. Phase 3: A study of the potential of losing the vehicle during nominal operation. Volume 5: Auxiliary shuttle risk analyses

Volume 5 is Appendix C, Auxiliary Shuttle Risk Analyses, and contains the following reports: Probabilistic Risk Assessment of Space Shuttle Phase 1 - Space Shuttle Catastrophic Failure Frequency Final Report; Risk Analysis Applied to the Space Shuttle Main Engine - Demonstration Project for the Main Combustion Chamber Risk Assessment; An Investigation of the Risk Implications of Space Shuttle Solid Rocket Booster Chamber Pressure Excursions; Safety of the Thermal Protection System of the Space Shuttle Orbiter - Quantitative Analysis and Organizational Factors; Space Shuttle Main Propulsion Pressurization System Probabilistic Risk Assessment, Final Report; and Space Shuttle Probabilistic Risk Assessment Proof-of-Concept Study - Auxiliary Power Unit and Hydraulic Power Unit Analysis Report.

Fragola, Joseph R.↗
DOE OSTI2025

EVALUATION OF HRA METHODOLOGIES FOR APPLICATION IN SDP WORK

This study critically evaluates human reliability analysis (HRA) methodologies applicable to regulatory probabilistic safety assessment (PSA) model, with a particular focus on their role in supporting the significance determination process (SDP) in nuclear safety assessment. Firstly, three widely utilized HRA methods – IDHEAS-ECA, SPAR-H, and ASEP/THERP – were qualitatively and quantitatively assessed. Qualitative assessments were conducted using attributes from the NEA/CSNI/R(2015)1 report, while quantitative evaluations employed regression and correlation analyses to compare predicted human error probabilities (HEPs) against empirical data. Results reveal distinct strengths, for example, IDHEAS-ECA’s robust predictive accuracy and K-HRA’s alignment with operational practices. In addition, dependency analysis and recovery analysis were critically evaluated. For dependency analysis, the methods’ handling of inter-task dependencies and their impact on HEPs were examined, while recovery analysis highlighted strategies for mitigating failure events. Furthermore, strategies were proposed to evaluate performance-shaping factors under conditions of reduced human performance, such as stress, fatigue, or cognitive overload, addressing specific challenges faced in SDP evaluations. Human errors from KINS’s operational performance information system event reports were evaluated as a case study. This study identifies gaps and provides actionable insights to ensure their validity and applicability in SDP HRA applications. This paper is a part of research conducted by KINS, and it should be noted that this result does not represent the regulatory position of KINS.

99 - GENERAL AND MISCELLANEOUS↗
NASA NTRS2008

Logistics Modeling for Lunar Exploration Systems

The extensive logistics required to support extended crewed operations in space make effective modeling of logistics requirements and deployment critical to predicting the behavior of human lunar exploration systems. This paper discusses the software that has been developed as part of the Campaign Manifest Analysis Tool in support of strategic analysis activities under the Constellation Architecture Team - Lunar. The described logistics module enables definition of logistics requirements across multiple surface locations and allows for the transfer of logistics between those locations. A key feature of the module is the loading algorithm that is used to efficiently load logistics by type into carriers and then onto landers. Attention is given to the capabilities and limitations of this loading algorithm, particularly with regard to surface transfers. These capabilities are described within the context of the object-oriented software implementation, with details provided on the applicability of using this approach to model other human exploration scenarios. Some challenges of incorporating probabilistics into this type of logistics analysis model are discussed at a high level.

Andraschko, Mark R.↗
NASA NTRSDate not supplied

Supply and Resource Management to Progressively Enable EIMO

BACKGROUND: Current medical operations in Low Earth Orbit (LEO) allow for real-time audio-video communication with a flight surgeon at mission control, resupply, and medical evacuation to earth on the order of hours. As mission profiles change from LEO to the Moon, Mars, and beyond, medical risk as a contribution to overall mission risk is anticipated to rise substantially. Concurrently, due to the distance, the medical systems on board vehicles proposed for these mission types are expected to have reduced mass and volume allocation. Together, astronaut crews will be at a higher risk of major medical events, be required to perform a broader set of tasks, and have substantially reduced resources and support to do so. Earth Independent Medical Operations (EIMO) aims to identify and fill the gaps present in this progressively changing paradigm. OVERVIEW: Medical supplies, resources, and skills are central to spaceflight medical systems. Vehicles used for non-LEO missions are anticipated to be smaller and thus the medical system will also need to have reduced mass, volume, and power. Medical resources are another form of consumable and may need resupply or pre-deployment to meet crew needs. One particular concern is the degradation of medications which become less efficacious and potentially toxic with time, particularly given environmental conditions such as temperature, humidity, oxygen, and radiation which have not yet been fully studied. Supply and resource management in LEO is dependent on resupply, however the supply chain of transporting equipment does not yet have a clear infrastructure for missions beyond LEO. DISCUSSION: EIMO is intended to systemically identify and fill these gaps with forward-looking solutions. In mission monitoring of resources with technology like RFID, improving medical resource longevity, targeted resupply and careful pre-mission planning will be central to facilitate crew health and performance. One approach to optimizing resources is the Informing Mission Planning via Analysis of Complex Tradespaces (IMPACT) tool, which uses probabilistic risk assessment (PRA) to quantitatively predict medical risk and identify resources and skills that mitigate this risk. This evidence based, quantitative analysis prediction tool and several other approaches to meeting the challenge of supply and resource management are discussed.

Arian Anderson↗
NASA NTRS1992

A new response surface approach for structural reliability analysis

This paper describes a new approach for computing structural reliability by post-processing previously computed probabilistic results for stress and strength. The objective is to provide an accurate method whereby independent probabilistic analyses for stress and strength functions can be performed independently and combined at a later time to compute probability of failure. The method provides a capability for testing different strength measures without the need for re-computing the probabilistic stress response. The proposed approach takes full account of the basic random variables effecting both stress and strength, and the failure region in the variable space identified during separate stress/strength probabilistic analyses. A simple closed-form example and a more complex analysis of a turbine blade subject to creep rupture is used to illustrate the method.

Thacker, B. H.↗
DOE OSTI2026

Re-evaluating probable maximum precipitation estimates: sensitivity to transposition domains and storm rotation using modern datasets

This study examines the sensitivity of Probable Maximum Precipitation (PMP) estimates to key methodological decisions embedded in the legacy approach adopted in the U.S. National Weather Service Hydrometeorological Reports No. 51 and No. 52. Although widely used for infrastructure design and risk regulation, fundamental aspects of PMP estimation—such as storm sample size, transposition domain, maximization procedures, and storm rotation—remain poorly constrained and lack formal guidance. Using the Red Rock watershed in Iowa as a case study, and leveraging the 2002–2023 NOAA Analysis of Record for Calibration (AORC) precipitation dataset, we systematically evaluate how each methodological choice, individually and in combination, influences PMP estimates. Our findings demonstrate that PMP is not a fixed physical upper bound but rather a modeling construct shaped heavily by user-defined assumptions. Notably, PMP values derived from modern gridded rainfall datasets can be substantially higher than the legacy estimate used in the original spillway design for Red Rock Dam. Decisions regarding storm sample size, domain extent, climatological window, and particularly storm rotation all contributed to higher PMP estimates. Storm rotation alone—a loosely constrained element in the current PMP practice—can amplify PMP by more than 25%. These results reveal the lack of standardized bounds in current PMP workflows and the need for systematic sensitivity and uncertainty analysis. As PMP estimation shifts toward probabilistic approaches, incorporating physically meaningful storm attributes will be key to developing more transparent, defensible methods for dam safety and climate-resilient infrastructure.

Probable maximum precipitation↗
DOE OSTI2024

Copacabana: a probabilistic membership assignment method for galaxy clusters

Cosmological analyses using galaxy clusters in optical/near-infrared photometric surveys require robust characterization of their galaxy content. Precisely determining which galaxies belong to a cluster is crucial. In this paper, we present the COlor Probabilistic Assignment of Clusters And BAyesiaN Analysis (Copacabana) algorithm. Copacabana computes membership probabilities for all galaxies within an aperture centred on the cluster using photometric redshifts, colours, and projected radial probability density functions. We use simulations to validate Copacabana and we show that it achieves up to 89 per cent membership accuracy with a mild dependence on photometric redshift uncertainties and choice of aperture size. We find that the precision of the photometric redshifts has the largest impact on the determination of the membership probabilities followed by the choice of the cluster aperture size. We also quantify how much these uncertainties in the membership probabilities affect the stellar mass–cluster mass scaling relation, a relation that directly impacts cosmology. Using the sum of the stellar masses weighted by membership probabilities (⁠μ * ⁠) as the observable, we find that Copacabana can reach an accuracy of 0.06 dex in the measurement of the scaling relation at low redshift for a Legacy Survey of Space and Time type survey. These results indicate the potential of Copacabana and μ * to be used in cosmological analyses of optically selected clusters in the future.

79 ASTRONOMY AND ASTROPHYSICS↗