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At least 649 records · Page 36

Strainrange partitioning: A total strain range version

Procedures are presented for expressing the Strainrange Partitioning (SRP) method for creep fatigue life prediction in terms of total strain range. Inelastic and elastic strain-range - life relations are summed to give total strain-range - life relations. The life components due to inelastic strains are dealt with using conventional SRP procedures while the life components due to elastic strains are expressed as families of time-dependent terms for each type of SRP cycle. Cyclic constitutive material behavior plays an important role in establishing the elastic strain-range - life relations as well as the partitioning of the inelastic strains. To apply the approach, however, it is not necessary to have to determine the magnitude of the inelastic strain range. The total strain SRP approach is evaluated and verified using two nickel base superalloys, AF2-1DA and Rene 95. Excellent agreement is demonstrated between observed and predicted cyclic lifetimes with 70 to 80 percent of the predicted lives falling within factors of two of the observed lives. The total strain-range SRP approach should be of considerable practical value to designers who are faced with creep-fatigue problems for which the inelastic strains cannot be calculated with sufficient accuracy to make reliable life predictions by the conventional inelastic strain range SRP approach.

Halford, G. R.↗

Strainrange partitioning - A total strain range version

Procedures are presented for expressing the Strainrange Partitioning (SRP) method for creep fatigue life prediction in terms of total strain range. Inelastic and elastic strain-range - life relations are summed to give total strain-range - life relations. The life components due to inelastic strains are dealt with using conventional SRP procedures while the life components due to elastic strains are expressed as families of time-dependent terms for each type of SRP cycle. Cyclic constitutive material behavior plays an important role in establishing the elastic strain-range life relations as well as the partitioning of the inelastic strains. To apply the approach, however, it is not necessary to have to determine the magnitude of the inelastic strain range. The total strain SRP approach is evaluated and verified using two nickel base superalloys, AF2-1DA and Rene 95. Excellent agreement is demonstrated between observed and predicted cyclic lifetimes with 70 to 80 percent of the predicted lives falling within factors of two of the observed lives. The total strain-range SRP approach should be of considerable practical value to designers who are faced with creep-fatigue problems for which the inelastic strains cannot be calculated with sufficient accuracy to make reliable life predictions by the conventional inelastic strain range SRP approach.

Halford, G. R.↗

Novel composites for wing and fuselage applications

Probabilistic predictions based on the IPACS code are presented for the material and structural response of unnotched and notched, IM6/3501-6 Gr/Ep laminates. Comparisons of predicted and measured modulus and strength distributions are given for unnotched unidirectional, cross-ply and quasi-isotropic laminates. The predicted modulus distributions were found to correlate well with the test results for all three unnotched laminates. Correlations of strength distributions for the unnotched laminates are judged good for the unidirectional laminate and fair for the cross-ply laminate, whereas the strength correlation for the quasi-isotropic laminate is judged poor because IPACS did not have a progressive failure capability at the time this work was performed. The report also presents probabilistic and structural reliability analysis predictions for the strain concentration factor (SCF) for an open-hole, quasi-isotropic laminate subjected to longitudinal tension. A special procedure was developed to adapt IPACS for the structural reliability analysis. The reliability results show the importance of identifying the most significant random variables upon which the SCF depends, and of having accurate scatter values for these variables.

Sobel, L. H.↗

Distributed Wind Resource Assessment Framework: Functional Requirements and Metrics for Performance and Reliability Modeling

The focus of the distributed wind resource assessment (DWRA) performance framework is to first clarify the key parameters that define the wind resource for any distributed wind turbine project and then describe the loss and uncertainty factors associated with long-term performance of wind turbine projects. Next it will identify and define the key parameters required to analyze the operational performance of a project. This framework could then be the foundation for understanding the predictability of the power and revenue from a project. Improving the predictability and reliability of wind power generation and operations will reduce costs and potentially establish a framework to attract new capital to the distributed wind industry sector. This report is the first part of a research effort to investigate the impact that improved resource assessment and energy estimation for distributed wind can have on consumer confidence, cost of capital, cost of ownership and operations, perception of financial risk, and levelized cost of energy.

17 WIND ENERGY↗

Composite Overwrapped Pressure Vessels (COPV) Stress Rupture Test: Part 2

One of the major concerns for the aging Space Shuttle fleet is the stress rupture life of composite overwrapped pressure vessels (COPVs). Stress rupture life of a COPY has been defined as the minimum time during which the composite maintains structural integrity considering the combined effects of stress levels and time. To assist in the evaluation of the aging COPVs in the Orbiter fleet an analytical reliability model was developed. The actual data used to construct this model was from testing of COPVs constructed of similar, but not exactly same materials and pressure cycles as used on Orbiter vessels. Since no actual Orbiter COPV stress rupture data exists the Space Shuttle Program decided to run a stress rupture test to compare to model predictions. Due to availability of spares, the testing was unfortunately limited to one 40" vessel. The stress rupture test was performed at maximum operating pressure at an elevated temperature to accelerate aging. The test was performed in two phases. The first phase, 130 F, a moderately accelerated test designed to achieve the midpoint of the model predicted point reliability. A more aggressive second phase, performed at 160 F, was designed to determine if the test article will exceed the 95% confidence interval ofthe model. In phase 3, the vessel pressure was increased to above maximum operating pressure while maintaining the phase 2 temperature. After reaching enough effectives hours to reach the 99.99% confidence level of the model phase 4 testing began when the temperature was increased to greater than 170 F. The vessel was maintained at phase 4 conditions until it failed after over 3 million effect hours. This paper will discuss the results of this test, it's implications and possible follow-on testing.

Russell, Richard↗

Composite Overwrapped Pressure Vessels (COPV) Stress Rupture Test

One of the major concerns for the aging Space Shuttle fleet is the stress rupture life of composite overwrapped pressure vessels (COPVs). Stress rupture life of a COPV has been defined as the minimum time during which the composite maintains structural integrity considering the combined effects of stress levels and time. To assist in the evaluation of the aging COPVs in the Orbiter fleet an analytical reliability model was developed. The actual data used to construct this model was from testing of COPVs constructed of similar, but not exactly same materials and pressure cycles as used on Orbiter vessels. Since no actual Orbiter COPV stress rupture data exists the Space Shuttle Program decided to run a stress rupture test to compare to model predictions. Due to availability of spares, the testing was unfortunately limited to one 40" vessel. The stress rupture test was performed at maximum operating pressure at an elevated temperature to accelerate aging. The test was performed in two phases. The first phase, 130 F, a moderately accelerated test designed to achieve the midpoint of the model predicted point reliability. The more aggressive second phase, performed at 160 F was designed to determine if the test article will exceed the 95% confidence interval of the model. This paper will discuss the results of this test, it's implications and possible follow-on testing.

Russell, Richard↗

Uncertainty-Aware Machine Learning for Small-Angle X-ray Scattering Analysis in Autonomous Experimentation

Small-angle X-ray scattering (SAXS) is a powerful high-throughput characterization tool for probing nanoscale structure in native sample environments, providing real-time morphological information such as nanoparticle size and shape during synthesis. However, automated SAXS data analysis for extracting meaningful structural parameters is non-trivial and remains a bottleneck in closed-loop experimentation towards autonomous materials discovery, which demands fast, reliable, and uncertainty-aware data analysis. Here, we develop a machine-learning approach for automated SAXS analysis tailored to closed-loop nanoparticle synthesis. A Random Forest (RF) regression model is trained on 100,000 synthetic SAXS curves generated from polydisperse spherical nanoparticles with realistic background contributions. Using normalized one-dimensional SAXS intensity profiles as input, the RF model directly predicts nanoparticle radius, size polydispersity, and background parameters, while the ensemble standard deviation across trees provides built-in uncertainty quantification (UQ). On synthetic data, we show that combining fit-quality metrics (R 2 , MAE) with thresholds on prediction uncertainty reliably identifies accurate parameter estimates without access to ground truth. We then apply the trained model to 365 experimental SAXS profiles of citrate-reduced gold nanoparticles synthesized using an automated droplet-flow microreactor with in situ SAXS at a synchrotron beamline, classifying the results into high- and low-confidence subsets based on UQ metrics. Finally, we integrate RF-based SAXS analysis into a simulated closed-loop optimization campaign using Gaussian process Bayesian optimization to minimize nanoparticle polydispersity, benchmarking against conventional automated Levenberg–Marquardt fitting. The RF-guided campaign exhibits substantially faster convergence and lower relative opportunity cost (∼0.07 vs ∼0.3), demonstrating that uncertainty-aware machine-learning SAXS analysis significantly enhances the efficiency and robustness of autonomous nanomaterials synthesis workflows.

Bayesian optimization↗

Scale-Resolving Simulations of a Supersonic Retro-Propulsion Concept For Mars Entry, Descent, and Landing

Supersonic retro-propulsion (SRP) is a deceleration technology that could enable largerpayloads and potentially humans to be brought from space to the surface of Mars safely.Accurate and reliable CFD predictions are needed to help design future Mars entry, descent,and landing (EDL) vehicles due to the cost and limitations of wind tunnel tests. TypicalCFD approaches struggle at points along the Mars EDL trajectory with high enough altitude(low enough ambient pressure) that the SRP motor plumes are over-expanded. This workdemonstrates how high-order scale-resolving simulations on Cartesian AMR grids can provideaccurate and reliable time-averaged aerodynamic loads on the vehicle for this challengingflow regime. Greater than second order convergence in the time-averaged integrated axialforce𝐶𝐴is obtained across the three finest mesh resolutions simulated, and the estimateduncertainty is smaller than the unsteady standard deviation – demonstrating the accuracy andreliability of the method. Although costly, this approach can yield higher confidence in𝐶𝐴thanpreviously obtained in a reasonable turnaround time and is within reach for a few points in thetrajectory (i.e. Mach 2.4, 2.52, and 2.78). Further computational performance and numericalmethods improvements are needed to reduce the cost enough to bring this method into the EDLengineering design cycle.

S&M↗

Influence of alloy solidification path on melt pool behavior in additive manufacturing

Numerical models used to study transport phenomena in laser-powder bed fusion processes often rely on assumptions and simplifications to reduce their computational expense. One common simplification is in the description of latent heat evolution during the solid-liquid phase change (i.e., the solidification pathway), justified by the fact that the mushy zone thickness is similar to the numerical grid spacing used for continuum transport models. The lack of resolution of transport phenomena in the mushy zone motivates the use of computationally convenient solidification paths such as linear or sigmoidal relationships over pathways derived from fundamental solidification theory such as equilibrium or Scheil models. In the present work, an uncertainty quantification (UQ) framework is used to analyze the influence of solidification pathway selection on the solidification dynamics and melt pool geometries in laser based additive manufacturing (AM) of IN625. Results show the solidification pathway has a quantifiable influence on the cooling rate at the liquidus isotherm, mushy zone thickness, and solidification time. Due to similarities in the latent heat evolution at the beginning of solidification, the equilibrium and Scheil models predict similar cooling rates near the liquidus isotherm, however the wider freezing range of Scheil leads to a wider mushy zone compared to equilibrium. The non-physical latent heat release profiles of sigmoidal and linear paths lead to significant overpredictions of cooling rates at the liquidus isotherm compared to equilibrium and Scheil. Finally, these results indicate that careful consideration should be given to the choice of solidification pathway to ensure reliable model predictions.

36 MATERIALS SCIENCE↗

Pitfalls and Precautions When Using Predicted Failure Data for Quantitative Analysis of Safety Risk for Human Rated Launch Vehicles

Launch vehicle reliability analysis is largely dependent upon using predicted failure rates from data sources such as MIL-HDBK-217F. Reliability prediction methodologies based on component data do not take into account risks attributable to manufacturing, assembly, and process controls. These sources often dominate component level reliability or risk of failure probability. While consequences of failure is often understood in assessing risk, using predicted values in a risk model to estimate the probability of occurrence will likely underestimate the risk. Managers and decision makers often use the probability of occurrence in determining whether to accept the risk or require a design modification. Due to the absence of system level test and operational data inherent in aerospace applications, the actual risk threshold for acceptance may not be appropriately characterized for decision making purposes. This paper will establish a method and approach to identify the pitfalls and precautions of accepting risk based solely upon predicted failure data. This approach will provide a set of guidelines that may be useful to arrive at a more realistic quantification of risk prior to acceptance by a program.

Hatfield, Glen S.↗

Predicting Team Functioning in Long Term Space Missions Using Acoustic and Linguistic Measures

Maintaining optimal team functioning is critical for long-duration space exploration missions, yet traditional monitoring methods, such as self-reports and wearable sensors, often impose operational burdens or suffer from bias. This paper investigates a non-intrusive speech-based artificial intelligence (AI) framework to predict degradations in team functioning using data from the Human Exploration Research Analog (HERA) of the U.S. National Aeronautics and Space Administration (NASA). Using acoustic features, linguistic descriptors, and semantic embeddings, we evaluate static non-linear and temporal machine learning models to predict both objective (task accuracy) and subjective (self-reported efficacy and cohesion) team functioning outcomes. Results indicate that temporal models outperform static approaches, with prediction of objective task accuracy in Team Interaction Battery (TIB) improving from near chance to 71%. Self-reported outcomes, including team efficacy and cohesion, are predicted more reliably than task performance, achieving balanced accuracies of up to 85.56% and 78.12%, respectively, and are found to be most strongly associated with acoustic features. In a second interdependent task, the MMSEV–EVA, accuracies of up to 78% are achieved using temporal models with acoustic features. Furthermore, incorporating just 1–2 days of team-specific historical data systematically improved performance, and acoustic markers from informal pre-task interactions provided modest predictive gains. Finally, while automated preprocessing yielded viable accuracy, humancorrected data provided moderate performance gains, though transcription error rates did not significantly correlate with model performance. These findings highlight the potential of speech as a passive, high-fidelity monitoring tool for autonomous habitats.

Temporal modeling↗

An ultrareliable integrated digital computer for helicopters

The US Army Fault-Tolerant Architecture (AFTA) has been defined to meet real-time fault-tolerant processing requirements of future Army applications. AFTA is the enabling technology that will allow the Army to configure existing processors and other hardware to provide high throughput and ultrahigh reliability necessary for terrain-following/terrain-avoidance (TF/TA) and nap-of-the-earth (NOE) flight control and other advanced Army applications. A brief description of AFTA's relevant attributes and theory of operation is given. The systems engineering models which permit the configuration on an AFTA to meet mission requirements as they evolve are presented, along with an example of their use to engineer an AFTA configuration. The resulting AFTA configuration, its predicted throughput, reliability, availability, weight, power, volume, and life-cycle cost impact, and the effects of possible engineering tradeoffs are presented.

Harper, Richard E.↗

Electrochemistry-based Battery Modeling for Prognostics

Batteries are used in a wide variety of applications. In recent years, they have become popular as a source of power for electric vehicles such as cars, unmanned aerial vehicles, and commericial passenger aircraft. In such application domains, it becomes crucial to both monitor battery health and performance and to predict end of discharge (EOD) and end of useful life (EOL) events. To implement such technologies, it is crucial to understand how batteries work and to capture that knowledge in the form of models that can be used by monitoring, diagnosis, and prognosis algorithms. In this work, we develop electrochemistry-based models of lithium-ion batteries that capture the significant electrochemical processes, are computationally efficient, capture the effects of aging, and are of suitable accuracy for reliable EOD prediction in a variety of usage profiles. This paper reports on the progress of such a model, with results demonstrating the model validity and accurate EOD predictions.

battery↗

Near Field Summary and Analysis of the Third AIAA Sonic Boom Workshop Shock-Plume Interaction Case

The Third AIAA Sonic Boom Prediction Workshop was held during January 2020, on the weekend prior to the AIAA SciTech conference. The workshop had 23 participants whom represented 6 different counties and 18 unique organizations that included government, industry and academia. The workshop was attend by over 50 individuals. The motivation for the workshop stems from the goal of obtaining supersonic commercial overland flight. In order to replace the current prohibition, with a certification standard, an international effort is required to quantify the accuracy and reliability of prediction methods. The workshops also identify deficiencies in existing methods where further research should be focused. The workshop consisted of two days with the first day focused on nearfield CFD and the second day on propagation techniques. The nearfield CFD study included two configurations known as the biconvex and the C608. This paper provided a summary and comparison of the results for the shock-plume interaction case, also known as the biconvex case. Overall agreement between the participants was very good with the largest standard deviations due to a slight shift of the shock location, not the predicted strength of the shocks.

Melissa Carter↗

Propagation Analysis of the 3rd Sonic Boom Prediction Workshop Cases using sBOOM

The 3rd Sonic Boom Prediction Workshop was held on January 4-5, 2020 in conjunction with the AIAA SciTech conference. The workshop had 23 participants who represented 6 different countries and 18 unique organizations that included government, industry, and academia. The workshop was attended by over 50 individuals. The motivation for the workshop stems from the goal of obtaining supersonic commercial overland flight. In order to replace the current prohibition with a certification standard, an international effort is required to quantify the accuracy and reliability of prediction methods. The workshops also identify deficiencies in existing methods where further research should be focused. The workshop consisted of two days with the first day focused on near-field computational fluid dynamics (CFD) and the second day on propagation techniques. For the atmospheric propagation portion of the workshop, two required cases and one optional case were prescribed for the participants to exercise their propagation implementations. This paper presents and discusses the results that were obtained using the sonic boom propagation code sBOOM. Results show that sonic boom carpets could be much different under arbitrary atmospheric conditions as opposed to standard atmospheric conditions. Additionally, several unique features when using sBOOM are presented.

Sonic Boom↗

Long-term prediction test procedure for most ICs, based on linear response theory

Experimentally, thermal annealing is known to be a factor which enables a number of different integrated circuits (IC's) to recover their operating characteristics after suffering radiation damage in the space radiation environment; thus, decreasing and limiting long term cumulative total-dose effects. This annealing is also known to be accelerated at elevated temperatures both during and after irradiation. Linear response theory (LRT) was applied, and a linear response function (LRF) to predict the radiation/annealing response of sensitive parameters of IC's for long term (several months or years) exposure to the space radiation environment were constructed. Compressing the annealing process from several years in orbit to just a few hours or days in the laboratory is achieved by subjecting the IC to elevated temperatures or by increasing the typical spaceflight dose rate by several orders of magnitude for simultaneous radiation/annealing only. The accomplishments are as follows: (1) the test procedure to make predictions of the radiation response was developed; (2) the calculation of the shift in the threshold potential due to the charge distribution in the oxide was written; (3) electron tunneling processes from the bulk Si to the oxide region in an MOS IC were estimated; (4) in order to connect the experimental annealing data to the theoretical model, constants of the model of the basic annealing process were established; (5) experimental data obtained at elevated temperatures were analyzed; (6) time compression and reliability of predictions for the long term region were shown; (7) a method to compress test time and to make predictions of response for the nonlinear region was proposed; and (8) nonlinearity of the LRF with respect to log(t) was calculated theoretically from a model.

Litovchenko, V.↗

Characterization and verification of a two-body wave energy converter with a novel power take-off

The lack of high efficient, predictable and reliable power take-off (PTO) systems limits developments of ocean wave energy technology. In this paper, a two-body self-reacting wave energy converter (WEC) with a novel PTO is designed, modelled and implemented for efficiency enhancement. A novel mechanical motion rectifier (MMR) using a ball screw mechanism and an enclosed gear set is integrated to improve the energy harvesting efficiency and reliability by rectifying the oscillatory wave motion into unidirectional rotation of the generator. Detailed design and dynamic modelling for the proposed WEC are presented. A prototype of the PTO is tested in a dry lab to characterize and refine the dynamic modelling. The characterized PTO model is combined with the WEC model to create an overall system model. A water tank test is conducted to verify the overall system dynamics, which proves the accuracy of the model and shows the advantages of the proposed WEC on efficiency and predictability. Following the method of how the WEC system is characterized, performance prediction of the proposed WEC with MMR PTO can be achieved with high accuracy.

16 TIDAL AND WAVE POWER↗

Towards Principled Experimental Study of Autonomous Mobile Robots

We review the current state of research in autonomous mobile robots and conclude that there is an inadequate basis for predicting the reliability and behavior of robots operating in unengineered environments. We present a new approach to the study of autonomous mobile robot performance based on formal statistical analysis of independently reproducible experiments conducted on real robots. Simulators serve as models rather than experimental surrogates. We demonstrate three new results: 1) Two commonly used performance metrics (time and distance) are not as well correlated as is often tacitly assumed. 2) The probability distributions of these performance metrics are exponential rather than normal, and 3) a modular, object-oriented simulation accurately predicts the behavior of the real robot in a statistically significant manner.

Object-Oriented Simulation↗