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NASA NTRS1995

Probabilistic simulation of long term behavior in polymer matrix composites

A methodology to compute cumulative probability distribution functions (CDF) of fatigue life for different ratios, r of applied stress to the laminate strength based on first ply failure criteria has been developed and demonstrated. Degradation effects due to long term environmental exposure and mechanical cyclic loads are considered in the simulation process. A unified time-stress dependent multi-factor interaction equation model developed at NASA Lewis Research Center has been used to account for the degradation/aging of material properties due to cyclic loads. Fast probability integration method is used to perform probabilistic simulation of uncertainties. Sensitivity of fatigue life reliability to uncertainties in the primitive random variables are computed and their significance in the reliability based design for maximum life is discussed. The results show that the graphite/epoxy (0/+45/90) deg laminate with ply thickness 0.125 in. has 500,000 cycles life for applied stress to laminate strength ratio of 0.6 and a reliability of 0.999. Also, the fatigue life reliability has been found to be most sensitive to the ply thickness and matrix tensile strength. Tighter quality controls must therefore be enforced on ply thickness and matrix strength in order to achieve high reliability of the structure.

Shah, A. R.↗

NASA NTRS1999

Principal Investigator-in-a-Box

Human performance in orbit is currently limited by several factors beyond the intrinsic awkwardness of motor control in weightlessness. Cognitive functioning can be affected by such factors as cumulative sleep loss, stress and the psychological effects of long-duration small-group isolation. When an astronaut operates a scientific experiment, the performance decrement associated with such factors can lead to lost or poor quality data and even the total loss of a scientific objective, at great cost to the sponsors and to the dismay of the Principal Investigator. In long-duration flights, as anticipated on the International Space Station and on any planetary exploration, the experimental model is further complicated by long delays between training and experiment, and the large number of experiments each crew member must perform. Although no documented studies have been published on the subject, astronauts report that an unusually large number of simple errors are made in space. Whether a result of the effects of microgravity, accumulated fatigue, stress or other factors, this pattern of increased error supports the need for a computerized decision-making aid for astronauts performing experiments. Artificial intelligence and expert systems might serve as powerful tools for assisting experiments in space. Those conducting space experiments typically need assistance exactly when the planned checklist does not apply. Expert systems, which use bits of human knowledge and human methods to respond appropriately to unusual situations, have a flexibility that is highly desirable in circumstances where an invariably predictable course of action/response does not exist. Frequently the human expert on the ground is unavailable, lacking the latest information, or not consulted by the astronaut conducting the experiment. In response to these issues, we have developed "Principal Investigator-in-a-Box," or [PI], to capture the reasoning process of the real expert, the Principal Investigator, and combine that with real-time data available in space in order to advise the astronaut about how to proceed in real time. [PI] advises the astronaut during the progress of an experiment in much the same way a real Principal Investigator might do while looking over the astronaut's shoulder. In its original application, [PI] mimicked several of the tasks of the Principal Investigator, including data quality monitoring, troubleshooting, prescheduling, protocol management and "interesting data" detection. The proposed research focuses on the efficacy of this technique as applied to the data quality monitoring and troubleshooting aspects of [PI].

Young, Laurence R.↗

NASA NTRS2010

Development of a Contingency Gas Analyzer for the Orion Crew Exploration Vehicle

NASA's experience with electrochemical sensors in a hand-held toxic gas monitor serves as a basis for the development of a fixed on-board instrument, the Contingency Gas Analyzer (CGA), for monitoring selected toxic combustion products as well as oxygen and carbon dioxide on the Orion Crew Exploration Vehicle (CEV). Oxygen and carbon dioxide are major components of the cabin environment and accurate measurement of these compounds is critical to maintaining a safe working environment for the crew. Fire or thermal degradation events may produce harmful levels of toxic products, including carbon monoxide (CO), hydrogen cyanide (HCN), and hydrogen chloride (HCl) in the environment. These three components, besides being toxic in their own right, can serve as surrogates for a panoply of hazardous combustion products. On orbit monitoring of these surrogates provides for crew health and safety by indicating the presence of toxic combustion products in the environment before, during and after combustion or thermal degradation events. Issues identified in previous NASA experiences mandate hardening the instrument and components to endure the mechanical and operational stresses of the CEV environment while maintaining high analytical fidelity. Specific functional challenges involve protecting the sensors from various anticipated events- such as rapid pressure changes, low cabin pressures, and extreme vibration/shock exposures- and extending the sensor lifetime and calibration periods far beyond the current state of the art to avoid the need for on-orbit calibration. This paper focuses on lessons learned from the earlier NASA hardware, current testing results, and engineering solutions to the identified problems. Of particular focus will be the means for protecting the sensors, addressing well known cross-sensitivity issues and the efficacy of a novel self monitoring mechanism for extending sensor calibration periods.

Niu, Bill↗

NASA NTRS2010

Utilizing In Situ Directional Hyperspectral Measurements to Validate Bio-Indicator Simulations for a Corn Crop Canopy

Two radiative transfer canopy models, SAIL and the two-layer Markov-Chain Canopy Reflectance Model (MCRM), were coupled with in situ leaf optical properties to simulate canopy-level spectral band ratio vegetation indices with the focus on the photochemical reflectance index in a cornfield. In situ hyperspectral measurements were made at both leaf and canopy levels. Leaf optical properties were obtained from both sunlit and shaded leaves. Canopy reflectance was acquired for eight different relative azimuth angles (psi) at three different view zenith angles (Theta (sub v)), and later used to validate model outputs. Field observations of photochemical reflectance index (PRI) for sunlit leaves exhibited lower values than shaded leaves, indicating higher light stress. Canopy PRI expressed obvious sensitivity to viewing geometry, as a function of both Theta (sub v) and psi . Overall, simulations from MCRM exhibited better agreements with in situ values than SAIL. When using only sunlit leaves as input, the MCRM-simulated PRI values showed satisfactory correlation and RMSE, as compared to in situ values. However, the performance of the MCRM model was significantly improved after defining a lower canopy layer comprised of shaded leaves beneath the upper sunlit leaf layer. Four other widely used band ratio vegetation indices were also studied and compared with the PRI results. MCRM simulations were able to generate satisfactory simulations for these other four indices when using only sunlit leaves as input; but unlike PRI, adding shaded leaves did not improve the performance of MCRM. These results support the hypothesis that the PRI is sensitive to physiological dynamics while the others detect static factors related to canopy structure. Sensitivity analysis was performed on MCRM in order to better understand the effects of structure related parameters on the PRI simulations. Leaf area index (LAI) showed the most significant impact on MCRM-simulated PRI among the parameters studied. This research shows the importance of hyperspectral and narrow band sensor studies, and especially the necessity of including the green wavelengths (e.g., 531 nm) on satellites proposing to monitor carbon dynamics of terrestrial ecosystems.

Cheng, Yen-Ben↗

NASA NTRSDate not supplied

Mapping Process Model Results to Fracture Model Initial Conditions for Adhesive Bonding

A systematic approach is proposed for mapping adhesive bonding process outcomes to initial conditions for progressive damage analysis (PDA). Herein, two mapping procedures are developed: 1) direct mapping for residual stresses, strains, and deformations obtained from a process model; and 2) functional mapping for quantities such as bondline thickness, degree of cure, and porosity that are assumed to have a functional relationship with fracture toughness but are not discretely modeled in the PDA. The spatial distribution of functionally mapped quantities may be determined by process modeling or inspection. The functional maps between the quantity of interest and fracture toughness may be obtained from independent lower-scale numerical simulations or empirical test campaigns. The proposed mapping procedure links the adhesive bonding process to the structural performance. Therefore, by accounting for the effects of bondline nonuniformities in structural analysis, analytical predictive accuracy can be improved, and off-nominal conditions can be evaluated. The mapping procedures are demonstrated and verified with example problems.

Andrew C Bergan↗

NASA NTRSDate not supplied

Mapping Process Model Results to Fracture Model Initial Conditions for Adhesive Bonding

Andrew Bergan↗

DOE OSTI2023

MODELS FOR ESTIMATING THE AUTOFRETTAGE PRESSURE AND RESIDUAL STRESSES IN WALLS OF TYPE 2 PRESSURE VESSELS

Autofrettage is a manufacturing process used during fabrication of Type 2 pressure vessels designed for usage at high pressures to enhance the fatigue life. The process locks high compressive residual stresses in the vessel’s liner wall that reduce the maximum and the mean stress during service loading. To achieve a consistent residual stress profile across the wall of the vessel, the choice of autofrettage pressure is critical. Several finite element analyses runs were conducted to estimate the correct autofrettage pressure that is a function of the yield strength of the liner material, the wall thickness, and the outside diameter of the liner for a wrap thickness of 17.06 mm (48 wire layers). From the finite element analyses results, models were developed to estimate the correct autofrettage pressure and the residual stress distribution across the liner wall as a function of the yield strength of the liner material, the wall thickness, and the outside diameter of the liner.

08 HYDROGEN↗

DOE OSTI2025

Increased inflammation as well as decreased endoplasmic reticulum stress and translation differentiate pancreatic islets from donors with pre-symptomatic stage 1 type 1 diabetes and non-diabetic donors

Aims/hypothesis Progression to type 1 diabetes is associated with genetic factors, the presence of autoantibodies and a decline in beta cell insulin secretion in response to glucose. Very little is known regarding the molecular changes that occur in human insulin-secreting beta cells prior to the onset of type 1 diabetes. Herein, we applied an unbiased proteomics approach to identify changes in proteins and potential mechanisms of islet dysfunction in islet-autoantibody-positive organ donors with pre-symptomatic stage 1 type 1 diabetes (HbA1c ≤42 mmol/mol [6.0%]). We aimed to identify pathways in islets that are indicative of beta cell dysfunction. Methods Multiple islet sections were collected through laser microdissection of frozen pancreatic tissues from organ donors positive for single or multiple islet autoantibodies (AAb + , n=5), and age (±2 years)- and sex-matched non-diabetic (ND) control donors (n=5) obtained from the Network for Pancreatic Organ donors with Diabetes (nPOD). Islet sections were subjected to MS-based proteomics and analysed with label-free quantification followed by pathway and functional annotations. Results Analyses resulted in ~4500 proteins identified with low false discovery rate (<1%), with 2165 proteins reliably quantified in every islet sample. We observed large inter-donor variations that presented a challenge for statistical analysis of proteome changes between donor groups. We therefore focused on only the donors with stage 1 type 1 diabetes who were positive for multiple autoantibodies (mAAb + , n=3) and genetic risk compared with their matched ND controls (n=3) for the final statistical analysis. Approximately 10% of the proteins (n=202) were significantly different (unadjusted p<0.025, q<0.15) for mAAb + vs ND donor islets. The significant alterations clustered around major functions for upregulation in the immune response and glycolysis, and downregulation in endoplasmic reticulum (ER) stress response as well as protein translation and synthesis. The observed proteome changes were further supported by several independent published datasets, including a proteomics dataset from in vitro proinflammatory cytokine-treated human islets and single-cell RNA-seq datasets from AAb + individuals. Conclusions/interpretation In situ human islet proteome alterations in stage 1 type 1 diabetes centred around several major functional categories, including an expected increase in immune response genes (elevated antigen presentation/HLA), with decreases in protein synthesis and ER stress response, as well as compensatory metabolic response. The dataset serves as a proteomics resource for future studies on beta cell changes during type 1 diabetes progression and pathogenesis. Data availability The LC-MS raw datasets that support the findings of this study have been deposited in the online repository: MassIVE (https://massive.ucsd.edu/ProteoSAFe/static/massive.jsp) with accession no. MSV000090212.

Autoantibody-positive↗

NASA NTRS2019

On the Use of Optimization Techniques for Turbulence Model Calibration

This article discusses the use of numerical optimization procedures to aid in the calibration of turbulence model coefficients. Such methods would increase the rigor and repeatability of the calibration procedure by requiring clearly defined and objective optimization metrics, and could be used to identify unique combinations of coefficient values for specific flow problems. The approach is applied to the re-calibration of an explicit algebraic Reynolds stress model for the incompressible planar mixing layer using the Nelder-Mead simplex algorithm and a micro-genetic algorithm with minimally imposed constraints. Three composite fitness functions, each based upon the error in the mixing layer growth rate and the normal and shear components of the Reynolds stresses, are investigated. The results demonstrate a significant improvement in the target objectives through the adjustment of three pressure-strain coefficients. Adjustments of additional coefficients provide little further benefit. Issues regarding the effectiveness of the fitness functions and the efficiency of the optimization algorithms are also discussed.

Yoder, Dennis A.↗

NASA NTRS1979

A numerical method for determination of source time functions for general three-dimensional rupture propagation

A method to determine the displacement and the stress on the crack plane for a three-dimensional shear crack of arbitrary shape propagating in an infinite, homogeneous medium which is linearly elastic everywhere off the crack plane is presented. The main idea of the method is to use a representation theorem in which the displacement at any given point on the crack plane is written as an integral of the traction over the whole crack plane. As a test of the accuracy of the numerical technique, the results are compared with known solutions for two simple cases.

Das, S.↗

NASA NTRS2001

Hindlimb unweighting affects rat vascular capacitance function

Microgravity is associated with an impaired stroke volume and, therefore, cardiac output response to orthostatic stress. We hypothesized that a decreased venous filling pressure due to increased venous compliance may be an important contributing factor in this response. We used a constant flow, constant right atrial pressure cardiopulmonary bypass procedure to measure total systemic vascular compliance (C(T)), arterial compliance (C(A)), and venous compliance (C(V)) in seven control and seven 21-day hindlimb unweighted (HLU) rats. These compliance values were calculated under baseline conditions and during an infusion of 0.2 microg*kg(-1)*min(-1) norepinephrine (NE). The change in reservoir volume, which reflects changes in unstressed vascular volume (DeltaV(0)) that occurred upon infusion of NE, was also measured. C(T) and C(V) were larger in HLU rats both at baseline and during the NE infusion (P < 0.05). Infusion of NE decreased C(T) and C(V) by ~20% in both HLU and control rats (P < 0.01). C(A) was also significantly decreased in both groups of rats by NE (P < 0.01), but values of C(A) were similar between HLU and control rats both at baseline and during the NE infusion. Additionally, the NE-induced DeltaV(0) was attenuated by 53% in HLU rats compared with control rats (P < 0.05). The larger C(V) and attenuated DeltaV(0) in HLU rats could contribute to a decreased filling pressure during orthostasis and thus may partially underlie the mechanism leading to the exaggerated fall in stroke volume and cardiac output seen in astronauts during an orthostatic stress after exposure to microgravity.

NASA Discipline Cardiopulmonary↗

DOE OSTI2023

Demonstration of acoustic monitoring for structural health of microreactors: Through use of neural networks and resonant ultrasound spectroscopy

Nuclear microreactors prioritize modularity and portability and are intended to be a cost-effective technology for non-conventional nuclear markets. As such, the development of microreactors into a safe and feasible solution for energy security applications will necessitate the development of non-destructive technologies to monitor the integrity of inaccessible reactors components during operation. This demonstration applies linear and nonlinear acoustic techniques, in combination with machine learning, to detect and classify mechanical changes (stress and damage) in a test article which are broadly representative of potential operating challenges within a functioning microreactor. All necessary data has been collected for this demonstration, with minor experimental issues identified that can be addressed in follow-on work. Motivated by the expected conditions within a functioning microreactor, we have demonstrated our monitoring techniques on a core-block-like test article using an unstructured excitation source that approximates the noisy acoustic environment expected during reactor operation. At all stress states mechanically applied to the test article, a machine learning model using an artificial neural network was able to classify with 100% accuracy whether a 3D laser vibrometry point measurement was made on an intact or artificially defective test article. Further, model predictions about whether the defect interface was rough or smooth were 95% accurate, indicating the ability of acoustic techniques to recover defect characteristics. Resonant ultrasound spectroscopy (RUS) was also applied to the dataset to provide further quantitative insights about material properties. RUS analysis was ultimately hampered by several minor experimental and data issues, limiting results to certain cases for this demonstration. Last, analysis using nonlinear RUS exhibited sensitivity to changing levels of applied stresses for each intact and defective state. As presented in this demonstration, acoustic monitoring exhibits sensitivity to stress changes, which are of concern due to high thermal gradients expected during startup and operation. Further, our techniques distinguish between measurements made on intact and damaged test articles.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

Seismicity and Stress Associated With a Fluid-Driven Fracture: Estimating the Evolving Geometry

A coupled approach, combining the theory of rate- and state-dependent friction and methods from poroelasticity, forms the basis for a quantitative relationship between displacements and fluid leak-off from a growing fracture and changes in the rate of seismic events in the region surrounding the fracture. Poroelastic Green's functions link fracture aperture changes and fluid flow from the fracture to changes in the stress field and pore pressure in the adjacent formation. The theory of rate- and state-dependent friction provides a connection between Coulomb stress changes and variations in the rate of seismic events. Numerical modeling indicates that the Coulomb stress changes can vary significantly between formations with differing properties. The relationship between the seismicity rate changes and the changes in the formation stresses and fluid pressure is nonlinear, but a transformation produces a quantity that is linearly related to the aperture changes and fluid leak-off from the fracture. The methodology provides a means for mapping changes in seismicity into fracture aperture changes and to image an evolving fracture. An application to observed microseismicity associated with a hydrofracture reveals asymmetric fracture propagation within two main zones, with extended propagation in the upper zone. Furthermore, the time-varying volume of the fracture agrees with the injected volume, given by the integration of rate changes at the injection well, providing validation of the estimated aperture changes.

58 GEOSCIENCES↗

DOE OSTI2024

A Comprehensive Stress Drop Map From Trench to Depth in the Northern Chilean Subduction Zone

We compute stress drops for earthquakes in Northern Chile recorded between 2007 and 2021. By applying two analysis techniques, (a) the spectral ratio (SR) method and (b) the spectral decomposition (SDC) method, a stress drop map for the subduction zone consisting of 51,510 stress drop values is produced. We build an extended set of empirical Green’s functions (EGF) for the SR method by systematic template matching. Outputs are used to compare with results from the SDC approach, where we apply cell-wise obtained global EGF's to compensate for the structural heterogeneity of the subduction zone. We find a good consistency of results of the two methods. The increased spatial coverage and quantity of stress drop estimates from the SDC method facilitate a consistent stress drop mapping of the different seismotectonic domains. Albeit only small differences of median stress drop, strike-perpendicular depth sections clearly reveal systematic variations, with earthquakes at different seismotectonic locations exhibiting distinct values. In particular, interface seismicity is characterized by the lowest observed median value, whereas upper plate earthquakes show noticeably higher stress drop values. Intermediate depth earthquakes show comparatively high average stress drop and a rather strong depth-dependent increase of median stress drop. Additionally, we observe spatio-temporal variability of stress drops related to the occurrence of the two megathrust earthquakes in the study region. The presented study is the first coherent large scale 3D stress drop mapping of the Northern Chilean subduction zone. It provides an important component for further detailed analysis of the physics of earthquake ruptures.

58 GEOSCIENCES↗

DOE OSTI2021

A prion-like protein regulator of seed germination undergoes hydration-dependent phase separation

Many organisms evolved strategies to survive desiccation. Plant seeds protect dehydrated embryos from various stressors and can lay dormant for millennia. Hydration is the key trigger to initiate germination, but the mechanism by which seeds sense water remains unresolved. Here we identified an uncharacterized Arabidopsis thaliana prion-like protein we named FLOE1, which phase separates upon hydration and allows the embryo to sense water stress. We demonstrate that biophysical states of FLOE1 condensates modulate its biological function in vivo in suppressing seed germination under unfavorable environments. We find intragenic, intraspecific, and interspecific natural variation in FLOE1 expression and phase separation and show that intragenic variation is associated with adaptive germination strategies in natural populations. This combination of molecular, organismal, and ecological studies uncovers FLOE1 as a tunable environmental sensor with direct implications for the design of drought-resistant crops, in the face of climate change.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Evidence for a genetic basis in functional trait tradeoffs with microbial growth rate but not growth yield

Tradeoffs in microbial functional traits have been a focus of recently described ecological frameworks and of mathematical models of microbial community functioning. Tradeoffs in key traits such as growth rate, growth yield, resource acquisition, and stress tolerance may have either a genetic basis or a physiological basis, and the type of tradeoff can inform how traits are modeled and measured. Here we provide evidence that growth rate/decomposition and growth rate/stress tolerance tradeoffs have a primarily genetic basis in a phylogenetically diverse suite of ten leaf litter-inhabiting fungi. In contrast, growth yield tradeoffs with functional traits are more likely to have a physiological basis. Consideration of the type of tradeoff, genetic or physiological, should help to inform efforts to model microbial contributions to ecosystem processes, especially when considering different scales. Consideration of physiological tradeoffs may be important for understanding short-term variability (e.g., pulse events) and fine spatial scales, whereas genetic tradeoffs are likely to be useful for understanding regional- to continental-scale and medium- to long-term contributions of microbes to ecosystem processes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Intermittent supplementation with fisetin improves arterial function in old mice by decreasing cellular senescence

Cellular senescence and the senescence-associated secretory phenotype (SASP) contribute to age-related arterial dysfunction, in part, by promoting oxidative stress and inflammation, which reduce the bioavailability of the vasodilatory molecule nitric oxide (NO). In the present study, we assessed the efficacy of fisetin, a natural compound, as a senolytic to reduce vascular cell senescence and SASP factors and improve arterial function in old mice. We found that fisetin decreased cellular senescence in human endothelial cell culture. In old mice, vascular cell senescence and SASP-related inflammation were lower 1 week after the final dose of oral intermittent (1 week on—2 weeks off—1 weeks on dosing) fisetin supplementation. Old fisetin-supplemented mice had higher endothelial function. Leveraging old p16-3MR mice, a transgenic model allowing genetic clearance of p16 INK4A -positive senescent cells, we found that ex vivo removal of senescent cells from arteries isolated from vehicle- but not fisetin-treated mice increased endothelium-dependent dilation, demonstrating that fisetin improved endothelial function through senolysis. Enhanced endothelial function with fisetin was mediated by increased NO bioavailability and reduced cellular- and mitochondrial-related oxidative stress. Arterial stiffness was lower in fisetin-treated mice. Ex vivo genetic senolysis in aorta rings from p16-3MR mice did not further reduce mechanical wall stiffness in fisetin-treated mice, demonstrating lower arterial stiffness after fisetin was due to senolysis. Lower arterial stiffness with fisetin was accompanied by favorable arterial wall remodeling. The findings from this study identify fisetin as promising therapy for clinical translation to target excess cell senescence to treat age-related arterial dysfunction.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1988

The fatigue damage behavior of a single crystal superalloy

The uniaxial fatigue behavior of a single crystal superalloy, PWA 1480, is described. Both monotonic tensile and constant amplitude fatigue tests were conducted at room temperature, in an effort to assess the applicability of polycrystalline-based fatigue life prediction methods to a single crystal superalloy. The observed constant amplitude behavior correlated best using a stress-based life criterion. Nearly all specimens failed at surface or slightly subsurface microporosity; this is thought to be responsible for the unusually large amount of scatter in the test results. An additional term is developed in the stress-life equation for the purpose of accounting for the effect of microporosity on fatigue life. The form chosen is a function of the effective area of the failure-producing microporosity projected on a plane perpendicular to the loading axis, as well as the applied stress. This additional term correlated the data to within factors of two on life. Although speculative, extrapolation of the microporosity relation to zero micropore area indicates that approximately an order of magnitude improvement in fatigue life should result.

Mcgaw, Michael A.↗