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At least 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

DEVELOP Poster: Medicine Bow Disasters

The Medicine Bow National Forest (MBNF) consists of approximately 1,383,790 acres of forested land, grassland, and sagebrush steppe in southeastern Wyoming. Cheatgrass (Bromus tectorum), an invasive plant species in the Western US, occurs in the grasslands throughout MBNF. Cheatgrass is known to rapidly colonize disturbed sites and dramatically alter historic fire regimes and nutrient/water dynamics as well as outcompete native plant species that are important forage for mule deer (Odocoileus hemionus) and elk (Cervus canadensis). In 2012, the Squirrel Creek Fire burned approximately 10,587 acres of land within MBNF, exacerbating the spread of cheatgrass. In 2015, the Wyoming Ecological Forecasting DEVELOP team identified areas of high cheatgrass abundance within the fire boundary in order to guide US Forest Service (USFS) herbicide spraying efforts to reduce cheatgrass in 2016. This research used Landsat 8 Operational Land Imager (OLI) and Sentinel-2 MultiSpectral Instrument (MSI) data to create a 2019 probabilistic cheatgrass occurrence map. This map allowed an analysis of the effectiveness of aerial spraying to inform future land management techniques for the USFS. Based on the results of the Generalized Linear Model, we found that treated areas decreased in cheatgrass cover by 36% while untreated areas increased in cheatgrass cover by 6%, suggesting that herbicide treatment has been effective.

Disasters↗
NASA NTRS2005

NESTEM Probabilistic Analysis Used to Study Mistuned Bladed Disks and Blisks With Aerodynamic and Structural Coupling

This document summarizes the initial results from a research effort at the NASA Glenn Research Center on blisk and bladed disk mistuning, including both structural and aerodynamic coupling. The structural coupling model is based on the Fundamental Mistuning Model (FMM, developed by Feiner and Griffin). This effort extends the FMM technique to accept aerodynamic coupling coefficients from computational fluid dynamic codes. The model was applied to a representative modern front compressor stage. Flutter stability and forced response were determined with structural coupling only, with aerodynamic coupling only, and with both structural and aerodynamic coupling. Tuned, randomly mistuned, and near alternately mistuned rotors were considered.

Kielb, Robert E.↗
NASA NTRS1991

Measuring the effects of distributed database models on transaction availability measures

Data distribution, data replication, and system reliability are key factors in determining the availability measures for transactions in distributed database systems. In order to simplify the evaluation of these measures, database designers and researchers tend to make unrealistic assumptions about these factors. Here, the effect of such assumptions on the computational complexity and accuracy of such evaluations is investigated. A database system is represented with five parameters related to the above factors. Probabilistic analysis is employed to evaluate the availability of read-one and read-write transactions. Both the read-one/write-all and the majority-read/majority-write replication control policies are considered. It is concluded that transaction availability is more sensitive to variations in degrees of replication, less sensitive to data distribution, and insensitive to reliability variations in a heterogeneous system. The computational complexity of the evaluations is found to be mainly determined by the chosen distributed database model, while the accuracy of the results are not so much dependent on the models.

Mukkamala, Ravi↗
DOE OSTI2021

Consensus Equilibrium for Subsurface Delineation

Heterogeneity and insufficient site characterization limit our knowledge of the subsurface. Inversion techniques, which minimize the mismatch between observations and model predictions, have become an essential tool of subsurface characterization. Most optimization-based approaches fail to incorporate various implicit priors and capture the geological complexity. We overcome these limitations by deploying the plug-and-play and consensus equilibrium (CE) strategies, which provide a flexible framework for image reconstruction. Our CE methodology for spatial delineation of geologic formations consists of an image denoiser and a variational auto-encoder (deep learning-based emulator). The former ameliorates the reconstruction noise, yielding well-defined geological structures; its mathematical equivalence with the proximal operator allows the deployment of advanced denoisers (e.g., CNN-based denoiser) that do not correspond to a regularization objective. The latter defines a geology prior that imposes a geological constraint, for example, continuity and shape of geological features, onto the reconstructed image. Here, we conduct a series of numerical experiments dealing with transient two-dimensional flow driven by a pumping well and natural hydraulic head gradient. They demonstrate the CE framework's ability to delineate, both probabilistically and deterministically, complex subsurface environments with sufficient quality.

42 ENGINEERING↗
DOE OSTI2024

Evaluation of FluSight influenza forecasting in the 2021–22 and 2022–23 seasons with a new target laboratory-confirmed influenza hospitalizations

Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. For the 2021–22 and 2022–23 influenza seasons, 26 forecasting teams provided national and jurisdiction-specific probabilistic predictions of weekly confirmed influenza hospital admissions for one-to-four weeks ahead. Forecast skill is evaluated using the Weighted Interval Score (WIS), relative WIS, and coverage. Six out of 23 models outperform the baseline model across forecast weeks and locations in 2021–22 and 12 out of 18 models in 2022–23. Averaging across all forecast targets, the FluSight ensemble is the 2nd most accurate model measured by WIS in 2021–22 and the 5th most accurate in the 2022–23 season. Forecast skill and 95% coverage for the FluSight ensemble and most component models degrade over longer forecast horizons. In this work we demonstrate that while the FluSight ensemble was a robust predictor, even ensembles face challenges during periods of rapid change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Using a 1D Radially Symmetric Coda Envelope Model for Robust Moment Magnitude ( M w ) Estimation in Iraq’s Tectonically Diverse Zones

Robust estimation of moment magnitude (M w ) can be challenging for Iraq due to the strong lateral heterogeneity across diverse tectonic zones. We aim to improve moment magnitude estimation by investigating the reliability of using a 1D coda envelope model in diverse tectonic zones of different lateral effects and offer a way forward for reliable estimates of M w for small events that are difficult to waveform model. Iraq comprises two main tectonic zones: (1) the Outer platform, consisting of the northwestern Zagros fold-thrust belt and the Mesopotamian foredeep, and (2) the Inner Arabian platform which is overlain by the Iraqi desert. A simple 1D coda envelope model was used because coda waves have a low sensitivity to the source and path heterogeneity. Three separate coda calibrations were conducted to investigate the robustness of a single 1D calibration to fit the country: Whole-region calibration, Zagros calibration, and Mesopotamia calibration. In the whole-region calibration, we used stations from both the Zagros and Mesopotamia zones. In the two other calibration models, we used only stations that were in those particular zones. Ground-truth reference spectra derived from the coda spectral ratio method were used to constrain high-frequency site terms. There was no drastic difference when comparing the moment magnitudes calculated from the waveform modeling and the three calibration models. The results show that the 1D coda envelope model is a reliable method even for a region with diverse tectonic zones. Therefore, we recommend using the whole-region calibration model for moment magnitude estimation that provides more complete path coverage and avoids biases introduced by path correction failures. The proposed calibration is a fundamental step in updating the comprehensive earthquake catalog and probabilistic seismic hazard assessments for Iraq.

58 GEOSCIENCES↗
DOE OSTI2021

Climate Intervention Assessment and Attribution

Focal Area(s): To ensure the US is positioned to scientifically attribute noncooperative climate interventions, we propose developing a foundational analytical framework for increased confidence in the assessment and attribution of observed changes in the climate. This framework will enable probabilistic attribution of prospective climate interventions. The target is to glean insight from complex Earth system data (Focal Area 3) by using AI to develop a prediction system comprised of a hierarchy of models (Focal Area 2).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

Probabilistic structural analysis of aerospace components using NESSUS

Probabilistic structural analysis of a Space Shuttle main engine turbopump blade is conducted using the computer code NESSUS (numerical evaluation of stochastic structures under stress). The goal of the analysis is to derive probabilistic characteristics of blade response given probabilistic descriptions of uncertainties in blade geometry, material properties, and temperature and pressure distributions. Probability densities are derived for critical blade responses. Risk assessment and failure life analysis is conducted assuming different failure models.

Shiao, Michael C.↗
NASA NTRS1988

Probabilistic structural analysis of aerospace components using NESSUS

Probabilistic structural analysis of a Space Shuttle main engine turbopump blade is conducted using the computer code NESSUS (numerical evaluation of stochastic structures under stress). The goal of the analysis is to derive probabilistic characteristics of blade response given probabilistic descriptions of uncertainties in blade geometry, material properties, and temperature and pressure distributions. Probability densities are derived for critical blade responses. Risk assessment and failure life analysis is conducted assuming different failure models.

Shiao, Michael C.↗
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 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 NTRSDate not supplied

Brace For Impact – It’s Coming, Do You Know What to Do With It?

Long-duration human exploration spaceflight missions to the Moon and Mars present unprecedented challenges for providing in-mission medical care. Compared with the International Space Station, the greater distance from Earth will mean increased mission durations, communication delays, limited to no resupply opportunities, and significant limitations on the evacuation of ill or injured crew. Spacecraft mass, volume, and power will be curtailed while higher demands will be placed on the crew’s knowledge, skills, and abilities. In this higher risk environment, it is important to define and quantitatively estimate human system risk attributable to medical conditions. IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a probabilistic risk assessment (PRA) and medical trade space analysis tool being developed by NASA to advance medical system design for exploration missions. IMPACT has made a number of enhancements on the Integrated Medical Model, the PRA tool currently used by NASA. These updates include a novel medical evidence base baselined to a long duration, deep space exploration environment; an expanded medical condition list; and a trade space analysis capability (e.g. comparing risk profiles and mass/volume constraints for medical capabilities and resources). IMPACT core functionality includes quantification of a medical capability set and assisting with identification of specific medical resources/hardware for exploration missions. In addition, IMPACT provides sophisticated trade space capabilities to estimate how human system risk varies with changes to the mission architecture or medical capability set. This presentation will provide a brief overview of the IMPACT tool, discuss representative use cases, and show example results.

Benjamin Easter↗
DOE OSTI2022

A Framework for Inverse Prediction Using Functional Response Data

Inverse prediction models have commonly been developed to handle scalar data from physical experiments. However, it is not uncommon for data to be collected in functional form. When data are collected in functional form, it must be aggregated to fit the form of traditional methods, which often results in a loss of information. For expensive experiments, this loss of information can be costly. In this study, we introduce the functional inverse prediction (FIP) framework, a general approach which uses the full information in functional response data to provide inverse predictions with probabilistic prediction uncertainties obtained with the bootstrap. The FIP framework is a general methodology that can be modified by practitioners to accommodate many different applications and types of data. We demonstrate the framework, highlighting points of flexibility, with a simulation example and applications to weather data and to nuclear forensics. Results show how functional models can improve the accuracy and precision of predictions.

42 ENGINEERING↗
DOE OSTI2022

Stochastic Learning Approach for Binary Optimization: Application to Bayesian Optimal Design of Experiments

Here, we present a novel stochastic approach to binary optimization suited for optimal experimental design (OED) for Bayesian inverse problems governed by mathematical models such as partial differential equations. The OED utility function, namely, the regularized optimality criterion, is cast into a stochastic objective function in the form of an expectation over a multivariate Bernoulli distribution. The probabilistic objective is then solved by using a stochastic optimization routine to find an optimal observational policy. This formulation (a) is generally applicable to binary optimization problems with soft constraints and is ideal for OED and sensor placement problems; (b) does not require differentiability of the original objective function (e.g., a utility function in OED applications) with respect to the design variable, and thus it enables direct employment of sparsity-enforcing penalty functions such as $\ell_0$, without needing to utilize a continuation procedure or apply a rounding technique; (c) exhibits much lower computational cost than traditional gradient-based relaxation approaches; and (d) can be applied to both linear and nonlinear OED problems with proper choice of the utility function. The proposed approach is analyzed from an optimization perspective with detailed convergence analysis of the optimization approach and is also analyzed from a machine learning perspective with correspondence to policy gradient reinforcement learning. The approach is demonstrated numerically by using an idealized two-dimensional Bayesian linear inverse problem and validated by extensive numerical experiments carried out for sensor placement in a parameter identification setup.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2004

Plan-graph Based Heuristics for Conformant Probabilistic Planning

In this paper, we introduce plan-graph based heuristics to solve a variation of the conformant probabilistic planning (CPP) problem. In many real-world problems, it is the case that the sensors are unreliable or take too many resources to provide knowledge about the environment. These domains are better modeled as conformant planning problems. POMDP based techniques are currently the most successful approach for solving CPP but have the limitation of state- space explosion. Recent advances in deterministic and conformant planning have shown that plan-graphs can be used to enhance the performance significantly. We show that this enhancement can also be translated to CPP. We describe our process for developing the plan-graph heuristics and estimating the probability of a partial plan. We compare the performance of our planner PVHPOP when used with different heuristics. We also perform a comparison with a POMDP solver to show over a order of magnitude improvement in performance.

Ramakrishnan, Salesh↗
NASA NTRS2003

Space Shuttle Main Engine Implications for the Abort-to-Orbit Off-the-Pad Study

In 2001, the Space Shuttle Main Engine (SSME) project office was contacted by the Space Shuttle Ascent Guidance, Navigation, and Control group to provide the engine perspective for an Abort-to-Orbit (ATO) study. The purpose of the AT0 Off-the-Pad study was to determine the feasibility of eliminating the Return to Launch Site and Transatlantic abort modes by using a five-segment solid rocket booster and throttling the remaining SSMEs to a higher power level. This would enable all abort modes to be Abort-to-Orbit. The SSME project office at Marshall Space Flight Center collaborated with MSFC's Space Transportation Directorate and Rocketdyne Propulsion and Power to provide the AT0 Off-the-Pad study with the analysis required. Power levels at 109%, 1 11% and 1 13% of rated power level were studied as well as mixture ratio decreases down to 5.85. SSME was to evaluate and define the technical and programmatic impacts to certify the SSME to these abort power levels. The SSME systems analysis group performed a steady state analysis using the SSME power balance model to determine if there were any technical issues associated with higher power level, low mixture ratio operation. Based on each power level/mixture ratio combination, an engine certification plan was created and a preliminary probabilistic risk assessment was performed. The results showed favorable results for higher power 1evel/lower mixture ratio SSME operation. In nearly all performance and redline parameters, the traded engine operation was encompassed by nominal engine performance of a prior engine configuration.

Schoffstoll, Dayna L.↗
DOE OSTI2022

An Approach to Dynamic Human Reliability Analysis using EMRALD Dynamic Risk Assessment Tool

Research for dynamic human reliability analysis (HRA) (a.k.a., simulation-based or computation-based HRA) has been required, as many researchers have emphasized the importance of dynamic approaches to probabilistic safety assessment (PSA). This study proposes the PRocedure-based Investigation Method of EMRALD Risk Assessment – Human Reliability Analysis (PRIMERA-HRA) method, which is an approach to dynamic HRA using the Event Modeling Risk Assessment using Linked Diagram (EMRALD) software developed by Idaho National Laboratory (INL). In this study, how to model human actions using the software and evaluate the error probabilities is suggested. The applicability of this approach will be also investigated through an extended loss of AC power (ELAP) scenario. Then, major insights from this dynamic HRA approach against the static one will be discussed in the paper.

99 GENERAL AND MISCELLANEOUS↗