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NASA NTRS1995

Expendable launch vehicle studies

Analytical support studies of expendable launch vehicles concentrate on the stability of the dynamics during launch especially during or near the region of maximum dynamic pressure. The in-plane dynamic equations of a generic launch vehicle with multiple flexible bending and fuel sloshing modes are developed and linearized. The information from LeRC about the grids, masses, and modes is incorporated into the model. The eigenvalues of the plant are analyzed for several modeling factors: utilizing diagonal mass matrix, uniform beam assumption, inclusion of aerodynamics, and the interaction between the aerodynamics and the flexible bending motion. Preliminary PID, LQR, and LQG control designs with sensor and actuator dynamics for this system and simulations are also conducted. The initial analysis for comparison of PD (proportional-derivative) and full state feedback LQR Linear quadratic regulator) shows that the split weighted LQR controller has better performance than that of the PD. In order to meet both the performance and robustness requirements, the H(sub infinity) robust controller for the expendable launch vehicle is developed. The simulation indicates that both the performance and robustness of the H(sub infinity) controller are better than that for the PID and LQG controllers. The modelling and analysis support studies team has continued development of methodology, using eigensensitivity analysis, to solve three classes of discrete eigenvalue equations. In the first class, the matrix elements are non-linear functions of the eigenvector. All non-linear periodic motion can be cast in this form. Here the eigenvector is comprised of the coefficients of complete basis functions spanning the response space and the eigenvalue is the frequency. The second class of eigenvalue problems studied is the quadratic eigenvalue problem. Solutions for linear viscously damped structures or viscoelastic structures can be reduced to this form. Particular attention is paid to Maxwell and Kelvin models. The third class of problems consists of linear eigenvalue problems in which the elements of the mass and stiffness matrices are stochastic. dynamic structural response for which the parameters are given by probabilistic distribution functions, rather than deterministic values, can be cast in this form. Solutions for several problems in each class will be presented.

Bainum, Peter M.↗

NASA NTRS2009

Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part II: Evaluation of Sample Models

Previous studies have shown that probabilistic forecasting may be a useful method for predicting persistent contrail formation. A probabilistic forecast to accurately predict contrail formation over the contiguous United States (CONUS) is created by using meteorological data based on hourly meteorological analyses from the Advanced Regional Prediction System (ARPS) and from the Rapid Update Cycle (RUC) as well as GOES water vapor channel measurements, combined with surface and satellite observations of contrails. Two groups of logistic models were created. The first group of models (SURFACE models) is based on surface-based contrail observations supplemented with satellite observations of contrail occurrence. The second group of models (OUTBREAK models) is derived from a selected subgroup of satellite-based observations of widespread persistent contrails. The mean accuracies for both the SURFACE and OUTBREAK models typically exceeded 75 percent when based on the RUC or ARPS analysis data, but decreased when the logistic models were derived from ARPS forecast data.

Duda, David P.↗

NASA NTRS2010

2009 Space Shuttle Probabilistic Risk Assessment Overview

Loss of a Space Shuttle during flight has severe consequences, including loss of a significant national asset; loss of national confidence and pride; and, most importantly, loss of human life. The Shuttle Probabilistic Risk Assessment (SPRA) is used to identify risk contributors and their significance; thus, assisting management in determining how to reduce risk. In 2006, an overview of the SPRA Iteration 2.1 was presented at PSAM 8 [1]. Like all successful PRAs, the SPRA is a living PRA and has undergone revisions since PSAM 8. The latest revision to the SPRA is Iteration 3. 1, and it will not be the last as the Shuttle program progresses and more is learned. This paper discusses the SPRA scope, overall methodology, and results, as well as provides risk insights. The scope, assumptions, uncertainties, and limitations of this assessment provide risk-informed perspective to aid management s decision-making process. In addition, this paper compares the Iteration 3.1 analysis and results to the Iteration 2.1 analysis and results presented at PSAM 8.

Hamlin, Teri L.↗

NASA NTRS1972

Reliability analysis applied to structural tests

The application of reliability theory to predict, from structural fatigue test data, the risk of failure of a structure under service conditions because its load-carrying capability is progressively reduced by the extension of a fatigue crack, is considered. The procedure is applicable to both safe-life and fail-safe structures and, for a prescribed safety level, it will enable an inspection procedure to be planned or, if inspection is not feasible, it will evaluate the life to replacement. The theory has been further developed to cope with the case of structures with initial cracks, such as can occur in modern high-strength materials which are susceptible to the formation of small flaws during the production process. The method has been applied to a structure of high-strength steel and the results are compared with those obtained by the current life estimation procedures. This has shown that the conventional methods can be unconservative in certain cases, depending on the characteristics of the structure and the design operating conditions. The suitability of the probabilistic approach to the interpretation of the results from full-scale fatigue testing of aircraft structures is discussed and the assumptions involved are examined.

Diamond, P.↗

NASA NTRS2020

Robustness Computation of Dynamic Controllability in Probabilistic Temporal Networks with Ordinary Distributions

Most existing works in Probabilistic Simple Temporal Networks (PSTNs) base their frameworks on well-defined probability distributions. This paper addresses on PSTN Dynamic Controllability (DC) robustness measure, i.e. the execution success probability of a network under dynamic control.We consider PSTNs where the probability distributions of the contingent edges are ordinary distributed (e.g. non-parametric, non-symmetric). We introduce the concepts of dispatching protocol (DP) as well as DP-robustness, the probability of success under a predefined dynamic policy.We propose a fixed-parameter pseudo-polynomial time algorithm to compute the exact DP-robustness of any PSTN under \textit{NextFirst} protocol, and apply to various PSTN datasets, including the real case of planetary exploration in the context of the Mars 2020 rover, and propose an original structural analysis.

Saint-Guillain, Michael↗

NASA NTRS2004

Effect of Clouds on Optical Imaging of the Space Shuttle During the Ascent Phase: A Statistical Analysis Based on a 3D Model

Clouds are highly effective in obscuring optical images of the Space Shuttle taken during its ascent by ground-based and airborne tracking cameras. Because the imagery is used for quick-look and post-flight engineering analysis, the Columbia Accident Investigation Board (CAIB) recommended the return-to-flight effort include an upgrade of the imaging system to enable it to obtain at least three useful views of the Shuttle from lift-off to at least solid rocket booster (SRB) separation (NASA 2003). The lifetimes of individual cloud elements capable of obscuring optical views of the Shuttle are typically 20 minutes or less. Therefore, accurately observing and forecasting cloud obscuration over an extended network of cameras poses an unprecedented challenge for the current state of observational and modeling techniques. In addition, even the best numerical simulations based on real observations will never reach "truth." In order to quantify the risk that clouds would obscure optical imagery of the Shuttle, a 3D model to calculate probabilistic risk was developed. The model was used to estimate the ability of a network of optical imaging cameras to obtain at least N simultaneous views of the Shuttle from lift-off to SRB separation in the presence of an idealized, randomized cloud field.

FROM↗

NASA NTRS2022

COMPACT KNN V2: Analogy-Based Cost Estimation Model for CubeSats

The CubeSat Or Microsat Probabilistic and AnalogiesCost Tool, or COMPACT, is a NASA Headquarters fundedeffort to fill the gap in cost estimating capabilities for CubeSats,as well as other microsat spacecraft. The COMPACT team hasfocused mainly on CubeSats to date, and has collected technical,programmatic and cost data on dozens of flown CubeSatsmissions led by NASA, research labs, and universities. In late2019, the team released the first tool prototype which uses a nonparametricregression technique, k-Nearest Neighbors (KNN),on actual data from historical CubeSat missions to produceearly ballpark analogy-based cost estimates for new CubeSatconcepts. Since the KNN prototype was first released, theCOMPACT team has normalized 17 new missions to be addedto the model in COMPACT V2. COMPACT V2 also featureschanges to the KNN tool algorithm including the introduction ofPrincipal Component Analysis (PCA) to the model developmentprocess and changes to the input parameters which have madethe analogy results more intuitive and have improved modelperformance. This paper describes the current COMPACTKNN dataset, improvements made to the model in COMPACTV2, an assessment of current model performance, and a forwardlook at COMPACT’s planned future enhancements.

Hooke, Melissa↗

NASA NTRSDate not supplied

Machine-Learning-Based Adaptive Thinning of CrIS Radiances to Improve Global Tropical Cyclone Analysis and Forecasts

This work is focused on optimizing the assimilation of hyperspectral infrared (IR) radiances from the Cross-track Infrared Sounder (CrIS) with the goal of improving the representation of tropical cyclones (TCs) in global analyses and forecasts. Current operational assimilation systems rely on subsampling IR radiances on a regular thinning grid. A new and improved adaptive methodology based on machine learning (ML) recognizes TCs from geostationary satellite imagery and is implemented in the Goddard Earth Observing System (GEOS) model and data assimilation framework. The ML methodology is extensively trained on existing TC data sets and creates for each TC a dynamic mask, based on the evolving shape and life cycle of that specific event. Once a TC mask is created, a switch is then activated in the data assimilation system to alter the thinning, ingesting more CrIS radiances within the moving mask, thus increasing the TC sampling. After the TC dissipates, the assimilation of CrIS radiances reverts to normal data density. Results of TC segmentation provided by a state-of-the-art generative machine learning model known as the Denoising Diffusion Probabilistic Model (DDPM) are compared to the previously used U-Net model. The new approach surpasses the performance of the previously developed one. The methodology is applied to both clear-sky and cloud-cleared radiances. Benefits from the latter methodology, particularly in improving the structure of TCs and the intensity forecasts, are presented.

Oreste Reale↗

NASA NTRS2008

The NASA Energy and Water Cycle Extreme (NEWSE) Integration Project

Skillful predictions of water and energy cycle extremes (flood and drought) are elusive. To better understand the mechanisms responsible for water and energy extremes, and to make decisive progress in predicting these extremes, the collaborative NASA Energy and Water cycle Extremes (NEWSE) Integration Project, is studying these extremes in the U.S. Southern Great Plains (SGP) during 2006-2007, including their relationships with continental and global scale processes, and assessment of their predictability on multiple space and time scales. It is our hypothesis that an integrative analysis of observed extremes which reflects the current understanding of the role of SST and soil moisture variability influences on atmospheric heating and forcing of planetary waves, incorporating recently available global and regional hydro- meteorological datasets (i.e., precipitation, water vapor, clouds, etc.) in conjunction with advances in data assimilation, can lead to new insights into the factors that lead to persistent drought and flooding. We will show initial results of this project, whose goals are to provide an improved definition, attribution and prediction on sub-seasonal to interannual time scales, improved understanding of the mechanisms of decadal drought and its predictability, including the impacts of SST variability and deep soil moisture variability, and improved monitoring/attributions, with transition to applications; a bridging of the gap between hydrological forecasts and stakeholders (utilization of probabilistic forecasts, education, forecast interpretation for different sectors, assessment of uncertainties for different sectors, etc.).

House, P. R.↗

NASA NTRSDate not supplied

Assessing Crew Medical Officer Preparedness for International Space Station Missions

INTRODUCTION Astronaut crew medical officers (CMO) undergo additional, specialized training to provide medical support onboard the International Space Station (ISS). CMO training focuses on utilizing resources on-station and optimizing communication with ground-based expertise to manage both common minor conditions as well as emergency/trauma situations. As NASA moves towards future Artemis and exploration class missions, we sought CMO perspectives on past, present, and future CMO training and medical resourcing to help inform mission planners regarding medical risk mitigation considerations. We present an interview-based qualitative assessment of CMO preparedness for the International Space Station with the aim to help iterate future training flows for Low Earth Orbit, Artemis, and exploration-class missions. METHODS A semi-structured interview tool was developed to assess CMO experience and their recommendations for future mission training considerations. Participants were recruited from former or current US astronauts who were designated as CMO and subsequently flew to the International Space Station. 10 former CMOs took part in the study. Interview transcripts were deidentified and evaluated for qualitative thematic analysis by two independent coders with NVivo Software suite (Lumivero, Denver, CO), and emergent themes were compiled. RESULTS Former CMO crew expressed appropriate preparedness for current ISS medical capabilities and requirements. They identified the role of the CMO as serving as a healthcare extender to ground-based flight surgeons for ISS and other LEO missions. Individuals with prior medical experience were preferred though not felt to be necessary for LEO missions. For exploration class missions with limitations in ground communication, a physician-as-CMO and more rigorous training curricula for both the CMO and astronaut crew were desired. DISCUSSION Former NASA astronaut crew were interviewed to retrospectively assess their preparedness as ISS crew medical officers and hypothesize future medical knowledge, skill, and ability needs. Along with medical operations subject matter expert opinion and advanced probabilistic risk assessment modeling, past CMO experience can help inform future CMO training considerations and responsibilities for future Artemis and exploration class missions.

M A Labarbera↗

NASA NTRS2010

Applying Monte Carlo Simulation to Launch Vehicle Design and Requirements Analysis

This Technical Publication (TP) is meant to address a number of topics related to the application of Monte Carlo simulation to launch vehicle design and requirements analysis. Although the focus is on a launch vehicle application, the methods may be applied to other complex systems as well. The TP is organized so that all the important topics are covered in the main text, and detailed derivations are in the appendices. The TP first introduces Monte Carlo simulation and the major topics to be discussed, including discussion of the input distributions for Monte Carlo runs, testing the simulation, how many runs are necessary for verification of requirements, what to do if results are desired for events that happen only rarely, and postprocessing, including analyzing any failed runs, examples of useful output products, and statistical information for generating desired results from the output data. Topics in the appendices include some tables for requirements verification, derivation of the number of runs required and generation of output probabilistic data with consumer risk included, derivation of launch vehicle models to include possible variations of assembled vehicles, minimization of a consumable to achieve a two-dimensional statistical result, recontact probability during staging, ensuring duplicated Monte Carlo random variations, and importance sampling.

Hanson, J. M.↗

NASA NTRS2022

NASA's NMME-Based S2S Hydrologic Forecast System for Food Insecurity Early Warning in Southern Africa

In situ hydrologic monitoring over regions most susceptible to food insecurity can be a challenge in current times due to various socio-economic and political issues in combination with environmental factors such as ongoing famine or drought. Hydrologic monitoring and initializing forecasts based on remotely sensed and analyzed data can contribute significantly to early warning in such regions. Routine hydrologic forecasts, as provided by NASA’s Hydrologic Forecasting and Analysis System (NHyFAS), are a recent addition to early warning systems. A custom instance of NHyFAS, termed FLDAS-Forecast, is used by FEWS NET’s Land Data Assimilation System (FLDAS). The FLDAS-Forecast’s dynamic forecasting component was originally set up with Goddard Earth Observing System (GEOS) forecast inputs and has been recently expanded with precipitation forecast forcing from the North American Multi-Model Ensemble (NMME). This paper describes the improvements in seasonal hydrologic forecasts produced with this updated system. Evaluations in this study focus on soil moisture across southern Africa’s growing season. Soil moisture forecasts are benchmarked and evaluated relative to climatology-based forecasts and historic runs, which are driven by observation-based meteorological forcing fields, and they are verified with remotely sensed observations of soil moisture and vegetation. Through multiple deterministic and probabilistic skill assessments, we show that using the larger ensemble of NMME precipitation inputs in the forecast system results in higher quality hydrologic forecasts than are allowed by climatology- or GEOS-only-based forecasts. Further, the near-real-time NMME-based rootzone soil moisture forecasts were able to correctly predict developing drought conditions over southern Africa through late 2019 and into early 2020.

Hydrologic forecasts↗

NASA NTRS1994

Stochastic decision analysis

Small space flight project design at NASA Langley Research Center goes through a multi-phase process from preliminary analysis to flight operations. The process insures that each system achieves its technical objectives with demonstrated quality and within planned budgets and schedules. A key technical component of early phases is decision analysis, which is a structure procedure for determining the best of a number of feasible concepts based upon project objectives. Feasible system concepts are generated by the designers and analyzed for schedule, cost, risk, and technical measures. Each performance measure value is normalized between the best and worst values and a weighted average score of all measures is calculated for each concept. The concept(s) with the highest scores are retained, while others are eliminated from further analysis. This project automated and enhanced the decision analysis process. Automation of the decision analysis process was done by creating a user-friendly, menu-driven, spreadsheet macro based decision analysis software program. The program contains data entry dialog boxes, automated data and output report generation, and automated output chart generation. The enhancements to the decision analysis process permit stochastic data entry and analysis. Rather than enter single measure values, the designers enter the range and most likely value for each measure and concept. The data can be entered at the system or subsystem level. System level data can be calculated as either sum, maximum, or product functions of the subsystem data. For each concept, the probability distributions are approximated for each measure and the total score for each concept as either constant, triangular, normal, or log-normal distributions. Based on these distributions, formulas are derived for the probability that the concept meets any given constraint, the probability that the concept meets all constraints, and the probability that the concept is within a given amount of the best score. Formulas are also derived for the probability that one concept's total score is within a given amount of a second concept's total score. These probabilistic calculations provide more realistic data entry and output information for designers, enabling designers to better determine which concepts to eliminate and which concepts to retain at the decision points of each design phase.

Lacksonen, Thomas A.↗

NASA NTRS1993

The application of structural reliability techniques to plume impingement loading of the Space Station Freedom Photovoltaic Array

A new aerospace application of structural reliability techniques is presented, where the applied forces depend on many probabilistic variables. This application is the plume impingement loading of the Space Station Freedom Photovoltaic Arrays. When the space shuttle berths with Space Station Freedom it must brake and maneuver towards the berthing point using its primary jets. The jet exhaust, or plume, may cause high loads on the photovoltaic arrays. The many parameters governing this problem are highly uncertain and random. An approach, using techniques from structural reliability, as opposed to the accepted deterministic methods, is presented which assesses the probability of failure of the array mast due to plume impingement loading. A Monte Carlo simulation of the berthing approach is used to determine the probability distribution of the loading. A probability distribution is also determined for the strength of the array. Structural reliability techniques are then used to assess the array mast design. These techniques are found to be superior to the standard deterministic dynamic transient analysis, for this class of problem. The results show that the probability of failure of the current array mast design, during its 15 year life, is minute.

Yunis, Isam S.↗

NASA NTRS1993

The Application of Structural Reliability Techniques to Plume Impingement Loading of the Space Station Freedom Photovoltaic Array

Yunis, Isam S.↗

NASA NTRS2010

Analysis of a Hypergolic Propellant Explosion During Processing of Launch Vehicles in the VAB

NASA is developing launch vehicles to support missions to Low Earth Orbit (LEO), the moon and deep space. Whether manned or unmanned, the vehicle components will likely be integrated in the Vehicle Assembly Building (VAB) at Kennedy Space Center (KSC) and typically include a fueled spacecraft (SC) that sits on top of one or more stages. The processing of a fueled SC involves hazardous operations when it is brought into the VAB Transfer Aisle and lifted a significant height for mating with lower stages. Accidents resulting from these hazardous operations could impact unrelated personnel working in buildings adjacent to the VAB. Safe separation distances based on the DOD Explosives Standards Quantity-Distance (Q-D) approach result in large IBD arcs. This paper presents site-specific air blast and fragmentation hazard analyses for comparison with the Q-D arcs as well as consequence and risk analyses to provide added information for the decision maker. A new physics-based fragmentation model is presented that includes: a) the development of a primary fragment list (which defines the fragment characteristics) associated with a hypergolic propellant explosion, b) a description of a 3D fragment bounce model, c) the results of probabilistic Monte-Carlo simulations (that include uncertainties in the fragment characteristics) to determine: i) the hazardous fragment density distance, ii) the expected number of wall/roof impacts and penetrations to over 40 buildings adjacent to the VAB, and iii) the risk to building occupants.

Chrostowski, Jon D.↗

NASA NTRS2004

Methodolgy For Evaluation Of Technology Impacts In Space Electric Power Systems

The Analysis and Management branch of the Power and Propulsion Office at NASA Glenn Research Center is responsible for performing complex analyses of the space power and In-Space propulsion products developed by GRC. This work quantifies the benefits of the advanced technologies to support on-going advocacy efforts. The Power and Propulsion Office is committed to understanding how the advancement in space technologies could benefit future NASA missions. They support many diverse projects and missions throughout NASA as well as industry and academia. The area of work that we are concentrating on is space technology investment strategies. Our goal is to develop a Monte-Carlo based tool to investigate technology impacts in space electric power systems. The framework is being developed at this stage, which will be used to set up a computer simulation of a space electric power system (EPS). The outcome is expected to be a probabilistic assessment of critical technologies and potential development issues. We are developing methods for integrating existing spreadsheet-based tools into the simulation tool. Also, work is being done on defining interface protocols to enable rapid integration of future tools. Monte Carlo-based simulation programs for statistical modeling of the EPS Model. I decided to learn and evaluate Palisade's @Risk and Risk Optimizer software, and utilize it's capabilities for the Electric Power System (EPS) model. I also looked at similar software packages (JMP, SPSS, Crystal Ball, VenSim, Analytica) available from other suppliers and evaluated them. The second task was to develop the framework for the tool, in which we had to define technology characteristics using weighing factors and probability distributions. Also we had to define the simulation space and add hard and soft constraints to the model. The third task is to incorporate (preliminary) cost factors into the model. A final task is developing a cross-platform solution of this framework.

Holda, Julie↗

NASA NTRS2013

Fracture Analysis of Particulate Reinforced Metal Matrix Composites

A fracture analysis of highly loaded particulate reinforced composites was performed using laser moire interferometry to measure the displacements within the plastic zone at the tip of an advancing crack. Ten castings were made of five different particulate reinforcement-aluminum alloy combinations. Each casting included net-shape specimens which were used for the evaluation of fracture toughness, tensile properties, and flexure properties resulting in an extensive materials properties data. Measured fracture toughness range from 14.1 MPa for an alumina reinforced 356 aluminum alloy to 23.9 MPa for a silicon carbide reinforced 2214 aluminum alloy. For the combination of these K(sub Ic) values and the measured tensile strengths, the compact tension specimens were too thin to yield true plane strain K(sub Ic) values. All materials exhibited brittle behavior characterized by very small tensile ductility suggesting that successful application of these materials requires that the design stresses be below the elastic limit. Probabilistic design principles similar to those used with ceramics are recommended when using these materials. Such principles would include the use of experimentally determined design allowables. In the absence of thorough testing, a design allowable stress of 60 percent of the measured ultimate tensile stress is recommended.

Min, James B.↗