Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “load uncertainty”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6

Population-based learning of load balancing policies for a distributed computer system

Effective load-balancing policies use dynamic resource information to schedule tasks in a distributed computer system. We present a novel method for automatically learning such policies. At each site in our system, we use a comparator neural network to predict the relative speedup of an incoming task using only the resource-utilization patterns obtained prior to the task's arrival. Outputs of these comparator networks are broadcast periodically over the distributed system, and the resource schedulers at each site use these values to determine the best site for executing an incoming task. The delays incurred in propagating workload information and tasks from one site to another, as well as the dynamic and unpredictable nature of workloads in multiprogrammed multiprocessors, may cause the workload pattern at the time of execution to differ from patterns prevailing at the times of load-index computation and decision making. Our load-balancing policy accommodates this uncertainty by using certain tunable parameters. We present a population-based machine-learning algorithm that adjusts these parameters in order to achieve high average speedups with respect to local execution. Our results show that our load-balancing policy, when combined with the comparator neural network for workload characterization, is effective in exploiting idle resources in a distributed computer system.

Mehra, Pankaj↗

Probabilistic Assessment of National Wind Tunnel

A preliminary probabilistic structural assessment of the critical section of National Wind Tunnel (NWT) is performed using NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) computer code. Thereby, the capabilities of NESSUS code have been demonstrated to address reliability issues of the NWT. Uncertainties in the geometry, material properties, loads and stiffener location on the NWT are considered to perform the reliability assessment. Probabilistic stress, frequency, buckling, fatigue and proof load analyses are performed. These analyses cover the major global and some local design requirements. Based on the assumed uncertainties, the results reveal the assurance of minimum 0.999 reliability for the NWT. Preliminary life prediction analysis results show that the life of the NWT is governed by the fatigue of welds. Also, reliability based proof test assessment is performed.

Shah, A. R.↗

Coupled Multi-Disciplinary Optimization for Structural Reliability and Affordability

A computational simulation method is presented for Non-Deterministic Multidisciplinary Optimization of engine composite materials and structures. A hypothetical engine duct made with ceramic matrix composites (CMC) is evaluated probabilistically in the presence of combined thermo-mechanical loading. The structure is tailored by quantifying the uncertainties in all relevant design variables such as fabrication, material, and loading parameters. The probabilistic sensitivities are used to select critical design variables for optimization. In this paper, two approaches for non-deterministic optimization are presented. The non-deterministic minimization of combined failure stress criterion is carried out by: (1) performing probabilistic evaluation first and then optimization and (2) performing optimization first and then probabilistic evaluation. The first approach shows that the optimization feasible region can be bounded by a set of prescribed probability limits and that the optimization follows the cumulative distribution function between those limits. The second approach shows that the optimization feasible region is bounded by 0.50 and 0.999 probabilities.

Abumeri, Galib H.↗

Optimization and simulation of flight control laws under parameter uncertainty and external disturbances

Several tasks pertinent to flight control in parameter uncertainty and wind-gust loading were successfully completed. Identification algorithms for extracting stability and control derivatives from flight data taking gust loading into account were developed. They were verified by simulation and evaluated throughly on actual flight data taken on a Lockheed Jet Star flying in turbulence. In particular the need for automatically generated dither-like inputs was studied. Criteria for performance evaluation using stochastic models were developed for gust alleviation as well as handling quantities. Algorithms for assessing degradation in performance due to parameter uncertainty were developed and evaluated using flight test data.

Source record↗

A Statistical Theory of Bidirectionality

Original concepts related to the quantification and assessment of bidirectionality in strain-gage balances were introduced by Ulbrich in 2012. These concepts are extended here in three ways: 1) the metric originally proposed by Ulbrich is normalized, 2) a categorical variable is introduced in the regression analysis to account for load polarity, and 3) the uncertainty in both normalized and non-normalized bidirectionality metrics is quantified. These extensions are applied to four representative balances to assess the bidirectionality characteristics of each. The paper is tutorial in nature, featuring reviews of certain elements of regression and formal inference. Principal findings are that bidirectionality appears to be a common characteristic of most balance outputs and that unless it is taken into account, it is likely to consume the entire error budget of a typical balance calibration experiment. Data volume and correlation among calibration loads are shown to have a significant impact on the precision with which bidirectionality metrics can be assessed.

DeLoach, Richard↗

Assuring Life in Composite Systems

A computational simulation method is presented to assure life in composite systems by using dynamic buckling of smart composite shells as an example. The combined use of composite mechanics, finite element computer codes, and probabilistic analysis enable the effective assessment of the dynamic buckling load of smart composite shells. A universal plot is generated to estimate the dynamic buckling load of composite shells at various load rates and probabilities. The shell structure is also evaluated with smart fibers embedded in the plies right below the outer plies. The results show that, on the average, the use of smart fibers improved the shell buckling resistance by about 9% at different probabilities and delayed the buckling occurrence time. The probabilistic sensitivities results indicate that uncertainties in the fiber volume ratio and ply thickness have major effects on the buckling load. The uncertainties in the electric field strength and smart material volume fraction have moderate effects and thereby in the assured life of the shell.

Chamis, Christos c.↗

Probabilistic Dynamic Buckling of Smart Composite Shells

A computational simulation method is presented to evaluate the deterministic and nondeterministic dynamic buckling of smart composite shells. The combined use of composite mechanics, finite element computer codes, and probabilistic analysis enable the effective assessment of the dynamic buckling load of smart composite shells. A universal plot is generated to estimate the dynamic buckling load of composite shells at various load rates and probabilities. The shell structure is also evaluated with smart fibers embedded in the plies right below the outer plies. The results show that, on the average, the use of smart fibers improved the shell buckling resistance by about 10 percent at different probabilities and delayed the buckling occurrence time. The probabilistic sensitivities results indicate that uncertainties in the fiber volume ratio and ply thickness have major effects on the buckling load while uncertainties in the electric field strength and smart material volume fraction have moderate effects. For the specific shell considered in this evaluation, the use of smart composite material is not recommended because the shell buckling resistance can be improved by simply re-arranging the orientation of the outer plies, as shown in the dynamic buckling analysis results presented in this report.

Abumeri, Galib H.↗

Probabilistic Dynamic Buckling of Smart Composite Shells

A computational simulation method is presented to evaluate the deterministic and nondeterministic dynamic buckling of smart composite shells. The combined use of intraply hybrid composite mechanics, finite element computer codes, and probabilistic analysis enable the effective assessment of the dynamic buckling load of smart composite shells. A universal plot is generated to estimate the dynamic buckling load of composite shells at various load rates and probabilities. The shell structure is also evaluated with smart fibers embedded in the plies right next to the outer plies. The results show that, on the average, the use of smart fibers improved the shell buckling resistance by about 10% at different probabilities and delayed the buckling occurrence time. The probabilistic sensitivities results indicate that uncertainties in the fiber volume ratio and ply thickness have major effects on the buckling load while uncertainties in the electric field strength and smart material volume fraction have moderate effects. For the specific shell considered in this evaluation, the use of smart composite material is not recommended because the shell buckling resistance can be improved by simply re-arranging the orientation of the outer plies, as shown in the dynamic buckling analysis results presented in this report.

Chamis, Christos C.↗

Trajectory-Based Loads for the Ares I-X Test Flight Vehicle

In trajectory-based loads, the structural engineer treats each point on the trajectory as a load case. Distributed aero, inertial, and propulsion forces are developed for the structural model which are equivalent to the integrated values of the trajectory model. Free-body diagrams are then used to solve for the internal forces, or loads, that keep the applied aero, inertial, and propulsion forces in dynamic equilibrium. There are several advantages to using trajectory-based loads. First, consistency is maintained between the integrated equilibrium equations of the trajectory analysis and the distributed equilibrium equations of the structural analysis. Second, the structural loads equations are tied to the uncertainty model for the trajectory systems analysis model. Atmosphere, aero, propulsion, mass property, and controls uncertainty models all feed into the dispersions that are generated for the trajectory systems analysis model. Changes in any of these input models will affect structural loads response. The trajectory systems model manages these inputs as well as the output from the structural model over thousands of dispersed cases. Large structural models with hundreds of thousands of degrees of freedom would execute too slowly to be an efficient part of several thousand system analyses. Trajectory-based loads provide a means for the structures discipline to be included in the integrated systems analysis. Successful applications of trajectory-based loads methods for the Ares I-X vehicle are covered in this paper. Preliminary design loads were based on 2000 trajectories using Monte Carlo dispersions. Range safety loads were tied to 8423 malfunction turn trajectories. In addition, active control system loads were based on 2000 preflight trajectories using Monte Carlo dispersions.

Vause, Roland F.↗

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system components

The fourth year of technical developments on the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) system for Probabilistic Structural Analysis Methods is summarized. The effort focused on the continued expansion of the Probabilistic Finite Element Method (PFEM) code, the implementation of the Probabilistic Boundary Element Method (PBEM), and the implementation of the Probabilistic Approximate Methods (PAppM) code. The principal focus for the PFEM code is the addition of a multilevel structural dynamics capability. The strategy includes probabilistic loads, treatment of material, geometry uncertainty, and full probabilistic variables. Enhancements are included for the Fast Probability Integration (FPI) algorithms and the addition of Monte Carlo simulation as an alternate. Work on the expert system and boundary element developments continues. The enhanced capability in the computer codes is validated by applications to a turbine blade and to an oxidizer duct.

Source record↗

Fatigue Reliability of Gas Turbine Engine Structures

The results of an investigation are described for fatigue reliability in engine structures. The description consists of two parts. Part 1 is for method development. Part 2 is a specific case study. In Part 1, the essential concepts and practical approaches to damage tolerance design in the gas turbine industry are summarized. These have evolved over the years in response to flight safety certification requirements. The effect of Non-Destructive Evaluation (NDE) methods on these methods is also reviewed. Assessment methods based on probabilistic fracture mechanics, with regard to both crack initiation and crack growth, are outlined. Limit state modeling techniques from structural reliability theory are shown to be appropriate for application to this problem, for both individual failure mode and system-level assessment. In Part 2, the results of a case study for the high pressure turbine of a turboprop engine are described. The response surface approach is used to construct a fatigue performance function. This performance function is used with the First Order Reliability Method (FORM) to determine the probability of failure and the sensitivity of the fatigue life to the engine parameters for the first stage disk rim of the two stage turbine. A hybrid combination of regression and Monte Carlo simulation is to use incorporate time dependent random variables. System reliability is used to determine the system probability of failure, and the sensitivity of the system fatigue life to the engine parameters of the high pressure turbine. 'ne variation in the primary hot gas and secondary cooling air, the uncertainty of the complex mission loading, and the scatter in the material data are considered.

Cruse, Thomas A.↗

Non-Deterministic Dynamic Instability of Composite Shells

A computationally effective method is described to evaluate the non-deterministic dynamic instability (probabilistic dynamic buckling) of thin composite shells. The method is a judicious combination of available computer codes for finite element, composite mechanics, and probabilistic structural analysis. The solution method is incrementally updated Lagrangian. It is illustrated by applying it to thin composite cylindrical shell subjected to dynamic loads. Both deterministic and probabilistic buckling loads are evaluated to demonstrate the effectiveness of the method. A universal plot is obtained for the specific shell that can be used to approximate buckling loads for different load rates and different probability levels. Results from this plot show that the faster the rate, the higher the buckling load and the shorter the time. The lower the probability, the lower is the buckling load for a specific time. Probabilistic sensitivity results show that the ply thickness, the fiber volume ratio and the fiber longitudinal modulus, dynamic load and loading rate are the dominant uncertainties, in that order.

Chamis, Christos C.↗

Dynamic Probabilistic Instability of Composite Structures

A computationally effective method is described to evaluate the non-deterministic dynamic instability (probabilistic dynamic buckling) of thin composite shells. The method is a judicious combination of available computer codes for finite element, composite mechanics and probabilistic structural analysis. The solution method is incrementally updated Lagrangian. It is illustrated by applying it to thin composite cylindrical shell subjected to dynamic loads. Both deterministic and probabilistic buckling loads are evaluated to demonstrate the effectiveness of the method. A universal plot is obtained for the specific shell that can be used to approximate buckling loads for different load rates and different probability levels. Results from this plot show that the faster the rate, the higher the buckling load and the shorter the time. The lower the probability, the lower is the buckling load for a specific time. Probabilistic sensitivity results show that the ply thickness, the fiber volume ratio and the fiber longitudinal modulus, dynamic load and loading rate are the dominant uncertainties in that order.

Chamis, Christos C.↗

Accuracy Assessments of Cloud Droplet Size Retrievals from Polarized Reflectance Measurements by the Research Scanning Polarimeter

We present an algorithm for the retrieval of cloud droplet size distribution parameters (effective radius and variance) from the Research Scanning Polarimeter (RSP) measurements. The RSP is an airborne prototype for the Aerosol Polarimetery Sensor (APS), which was on-board of the NASA Glory satellite. This instrument measures both polarized and total reflectance in 9 spectral channels with central wavelengths ranging from 410 to 2260 nm. The cloud droplet size retrievals use the polarized reflectance in the scattering angle range between 135deg and 165deg, where they exhibit the sharply defined structure known as the rain- or cloud-bow. The shape of the rainbow is determined mainly by the single scattering properties of cloud particles. This significantly simplifies both forward modeling and inversions, while also substantially reducing uncertainties caused by the aerosol loading and possible presence of undetected clouds nearby. In this study we present the accuracy evaluation of our algorithm based on the results of sensitivity tests performed using realistic simulated cloud radiation fields.

Rainbow↗

High Temperature Material Property Data and Challenges to Thermal Process Model Predictions and In-Situ/Ex-Situ Measurements for Metallic Additive Manufacturing

Understanding and predicting performance properties of parts produced by metallic additive manufacturing has improved significantly over the past decade; however, difficult to measure material properties and process outcomes continue to be challenges. The qualification or certification of aerospace parts require extensive measures to quantify variable part properties in order to buy down the risk of component failure. The variability, inherent to the additive manufacturing, process adds unwanted uncertainty in the production of load critical structural components. Process modeling has proven valuable in providing predictions and context for understanding outcomes of the additive manufacturing process; however, these physically informed process models require material properties at temperatures that are difficult to measure and rarely available. Further, calibrating or validating such models is difficult because the process itself is challenging to measure. This talk will explore some of the challenges resulting from difficult to acquire input data by relating thermal process model predictions to in-situ and ex-situ optical microscopy measurements.

Process Model↗

Current State of NASA Continuously Rotating Detonation Cycle Engine Development

NASA is currently investigating continuous detonation cycle engines for the application of lander and interplanetary space exploration missions. The performance benefits of a detonation cycle engine may allow for a broader design trade space and more compact geometry required for future missions to the Moon and onwards towards Mars. However, the technology readiness level (TRL) within the US was found to be low with several major risk factors that require understanding prior to full engine system development. One area of uncertainty is the extreme heat loads expected during thermal steady state conditions. To achieve this, an announcement for collaborative opportunity (ACO) partnership between IN Space LLC and NASA Marshall Space Flight Center (MSFC) was established to explore integration of additive manufacturing (AM) processes and the high conductance copper-based alloys, GRCop-42 and GRCop-84. This work outlines the hot fire testing of a 7K lbf thrust class fully AM GRCop-alloy rotating detonation rocket engine (RDRE). Two annular thrust chamber configurations emulating a lander engine system were tested with LOx/GH2 and LOx/LCH4. In both configurations, select hardware was actively cooled using de-ionized water and regeneratively cooled using LCH4. All primary hardware survived long duration tests to thermal steady state up to 133 seconds in a single burn. In total, 18 starts and 802 seconds of duration were achieved with and without visual confirmation of waves present. The proportion of burned propellant, or level of complete combustion, was found to be high compared to the theoretically achievable mean chamber pressure in all cases.

Thomas Teasley↗

Discrete distributed strain sensing of intelligent structures

Techniques are developed for the design of discrete highly distributed sensor systems for use in intelligent structures. First the functional requirements for such a system are presented. Discrete spatially averaging strain sensors are then identified as satisfying the functional requirements. A variety of spatial weightings for spatially averaging sensors are examined, and their wave number characteristics are determined. Preferable spatial weightings are identified. Several numerical integration rules used to integrate such sensors in order to determine the global deflection of the structure are discussed. A numerical simulation is conducted using point and rectangular sensors mounted on a cantilevered beam under static loading. Gage factor and sensor position uncertainties are incorporated to assess the absolute error and standard deviation of the error in the estimated tip displacement found by numerically integrating the sensor outputs. An experiment is carried out using a statically loaded cantilevered beam with five point sensors. It is found that in most cases the actual experimental error is within one standard deviation of the absolute error as found in the numerical simulation.

Anderson, Mark S.↗

Model Update of a Micro Air Vehicle (MAV) Flexible Wing Frame with Uncertainty Quantification

This paper describes a procedure to update parameters in the finite element model of a Micro Air Vehicle (MAV) to improve displacement predictions under aerodynamics loads. Because of fabrication, materials, and geometric uncertainties, a statistical approach combined with Multidisciplinary Design Optimization (MDO) is used to modify key model parameters. Static test data collected using photogrammetry are used to correlate with model predictions. Results show significant improvements in model predictions after parameters are updated; however, computed probabilities values indicate low confidence in updated values and/or model structure errors. Lessons learned in the areas of wing design, test procedures, modeling approaches with geometric nonlinearities, and uncertainties quantification are all documented.

Reaves, Mercedes C.↗