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At least 289 records · Page 16

A Hierarchical Approach to Fracture Mechanics

Recent research conducted under NASA LaRC's Creativity and Innovation Program has led to the development of an initial approach for a hierarchical fracture mechanics. This methodology unites failure mechanisms occurring at different length scales and provides a framework for a physics-based theory of fracture. At the nanoscale, parametric molecular dynamic simulations are used to compute the energy associated with atomic level failure mechanisms. This information is used in a mesoscale percolation model of defect coalescence to obtain statistics of fracture paths and energies through Monte Carlo simulations. The mathematical structure of predicted crack paths is described using concepts of fractal geometry. The non-integer fractal dimension relates geometric and energy measures between meso- and macroscales. For illustration, a fractal-based continuum strain energy release rate is derived for inter- and transgranular fracture in polycrystalline metals.

Saether, Erik↗

Operation Optimization using Reinforcement Learning with Integrated Artificial Reasoning Framework

In large and complex systems, operational decision-making requires a systematic analysis with a vast amount of data from both process parameters and component status monitoring. In this paper, we present an integrated artificial reasoning approach for system state transition models that can help operational decision-making with explainable and traceable reasoning. The integrated artificial reasoning framework is a physics-based approach of defining the system structure in a Bayesian network, so we leveraged it in a Markov decision process (MDP) for finding optimal operational solutions. In our proposed framework, the MDP is implemented on a dynamic Bayesian network (DBN), which represents causalities in a system. The multilevel flow modeling was utilized in order to extract these causalities in a more efficient and objective manner. Since multilevel flow modeling is based on the fundamental energy and mass conservation laws, the target system is decomposed into several mass, energy, and information structures, which serve as the basis for a DBN. The MDP consists of the processes of finding a solution for the Bellman equation, which can be derived from the conditional probability equations of the constructed DBN. System operators can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from the component degradation process or random failures. We analyzed a simplified example system to illustrate finding an optimal operational policy with this approach.

99 GENERAL AND MISCELLANEOUS↗

Role of reinforcement learning for risk-based robust control of cyber-physical energy systems

Critical infrastructures such as cyber-physical energy systems (CPS-E) integrate information flow and physical operations that are vulnerable to natural and targeted failures. Safe, secure, and reliable operation and control of CPS-E is critical to ensure societal well-being and economic prosperity. Automated control is key for real-time operations and may be mathematically cast as a sequential decision-making problem under uncertainty. Emergence of data-driven techniques for decision making under uncertainty, such as reinforcement learning (RL), have led to promising advances for addressing sequential decision-making problems for risk-based robust CPS-E control. However, existing research challenges include understanding the applicability of RL methods across diverse CPS-E applications, addressing the effect of risk preferences across multiple RL methods, and development of open-source domain-aware simulation environments for RL experimentation within a CPS-E context. This article systematically analyzes the applicability of four types of RL methods (model-free, model-based, hybrid model-free and model-based, and hierarchical) for risk-based robust CPS-E control. Problem features and solution stability for the RL methods are also discussed. We demonstrate and compare the performance of multiple RL methods under different risk specifications (risk-averse, risk-neutral, and risk-seeking) through the development and application of an open-source simulation environment. Motivating numerical simulation examples include representative single-zone and multizone building control use cases. Finally, six key insights for future research and broader adoption of RL methods are identified, with specific emphasis on problem features, algorithmic explainability, and solution stability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Comparison of Functional Models for Use in the Function-Failure Design Method

When failure analysis and prevention, guided by historical design knowledge, are coupled with product design at its conception, shorter design cycles are possible. By decreasing the design time of a product in this manner, design costs are reduced and the product will better suit the customer s needs. Prior work indicates that similar failure modes occur with products (or components) with similar functionality. To capitalize on this finding, a knowledge base of historical failure information linked to functionality is assembled for use by designers. One possible use for this knowledge base is within the Elemental Function-Failure Design Method (EFDM). This design methodology and failure analysis tool begins at conceptual design and keeps the designer cognizant of failures that are likely to occur based on the product s functionality. The EFDM offers potential improvement over current failure analysis methods, such as FMEA, FMECA, and Fault Tree Analysis, because it can be implemented hand in hand with other conceptual design steps and carried throughout a product s design cycle. These other failure analysis methods can only truly be effective after a physical design has been completed. The EFDM however is only as good as the knowledge base that it draws from, and therefore it is of utmost importance to develop a knowledge base that will be suitable for use across a wide spectrum of products. One fundamental question that arises in using the EFDM is: At what level of detail should functional descriptions of components be encoded? This paper explores two approaches to populating a knowledge base with actual failure occurrence information from Bell 206 helicopters. Functional models expressed at various levels of detail are investigated to determine the necessary detail for an applicable knowledge base that can be used by designers in both new designs as well as redesigns. High level and more detailed functional descriptions are derived for each failed component based on NTSB accident reports. To best record this data, standardized functional and failure mode vocabularies are used. Two separate function-failure knowledge bases are then created aid compared. Results indicate that encoding failure data using more detailed functional models allows for a more robust knowledge base. Interestingly however, when applying the EFDM, high level descriptions continue to produce useful results when using the knowledge base generated from the detailed functional models.

Stock, Michael E.↗

A fluid-structure interaction solver for investigating torsional galloping in solar-tracking photovoltaic panel arrays

Solar-tracking photovoltaic arrays are susceptible to aeroelastic fluttering during high-wind events. This dynamic fluttering behavior can grow in amplitude until the panels enter an unstable mode known as torsional galloping which can lead to panel failure or total array destruction. To better understand the physics of the torsional galloping phenomenon and to inform the discussion around panel design and recommended panel stow positions during high wind events, a fluid-structure interaction solver composed of a simulated atmospheric boundary layer with simplified panel structural responses was designed. The simulation choices and features of this solver were informed by the geometry and physical properties of an experimental panel array known to exhibit torsional galloping behavior during hind-wind events. Furthermore, these simulations revealed that the torsional galloping instability is driven by a combination of cyclic vortex shedding from the sun-facing side of the panel and the elastic properties of the torque tube linking the panel assemblies. Testing different stow angles across a range of wind speeds indicates that panels are generally more stable when stowed at negative angles where the leading edge is closer to the ground, hypothesized to be due to ground-blocking effects. These results are supplemented by a discussion of stability trends noted during testing and possible implications when considering multi-row array interactions.

14 SOLAR ENERGY↗

Using Models to Predict the Hygrothermal Performance of Equipment and Piping Insulation

The development of hygrothermal models began in earnest in the 1990s, with the initial emphasis on the performance of building envelope systems. Numerous large-scale building envelope failures associated with water intrusion drove this development. The physical principles of moisture transfer that apply to building envelopes are equally valid for equipment and piping insulation systems. The main advantage of modeling is that carefully characterized models can predict the long-term hygrothermal performance of any system under different climatic and interior conditions. Thermal insulations are commonly used on outdoor equipment and piping for different applications, such as thermal energy conservation and freeze protection. The insulated equipment usually experiences moisture intrusion due to many factors, such as the duration and frequency of moisture exposure, equipment operating temperature, insulation type, exposure temperature, weather conditions, equipment thermal cycling, and weatherproofing condition. Hygrothermal models have been employed to estimate the moisture pickup of insulated equipment and piping systems, as well as the moisture redistribution and subsequent change in thermal performance as these systems become contaminated with moisture. The hygrothermal model provides insights on the parameters influencing the time of wetness, the lateral redistribution of moisture along the pipe away from the leak, and the ease by which water escapes the insulation/jacketing systems. It has been shown that the moisture leak effect decreases rapidly with distance from the leak and that one- and two-dimensional hygrothermal simulations help to identify solutions to reduce conditions that support corrosion under insulation (CUI).

Shrestha, Som↗

Adhesion theory review

Bonding theories reviewed include physical adsorption, hydrogen bonding, chemisorption and surface energy; bond failure mechanisms include phase discontinuity, swelling and corrosion. Concept of bond failure by water desorption is introduced and discussed.

Delollis, N. J.↗

Analytical modeling of battery cycle life

An analytical model related to the physical and chemical processes involved in battery wear and failure is discussed. The model is described using the data from the Crane tests.

Gross, S.↗

Sensor/actuator failure detection and isolation for airbreathing propulsion systems

In this paper, the Generalized Likelihood Ratio (GLR) test is used to detect and isolate sensor and/or actuator failures when a digital computer simulation model of the physical system is available. The input to the GLR detector is an innovation sequence formed by subtracting the model outputs from the sensed outputs. Application of the GLR detector to the General Electric QCSEE turbofan engine demonstrates the utility of the proposed procedure.

Leininger, G. G.↗

Long-duration ballooning at mid-latitudes and in Antarctica

Since the latter 1980s, there have been only two NASA balloon program failures out of over 100 flights involving astrophysical, space physics and upper atmosphere research activities. Since the successful flight of the Gamma Ray Advanced Detector, numerous requests have been received for flights in the Antarctic region. Such long-duration flights would employ the standard zero-pressure balloon of 28 MCF two-cap type, which carries a 3000-lb nominal suspended weight to 130,000 ft. For Antarctica, the nominal science weight would be from 1500 lbs to as much as 1900 lbs, with some sacrifice in altitude.

Jones, W. V.↗

Torsion Tests of Tubes

This report presents the results of tests of 63 chromium-molybdenum steel tubes and 102 17st aluminum-alloy tubes of various sizes and lengths made to study the dependence of the torsional strength on both the dimensions of the tube and the physical properties of the tube material. Three types of failure are found to be important for sizes of tubes frequently used in aircraft construction: (1) failure by plastic shear, in which the tube material reached its yield strength before the critical torque was reached; (2) failure by elastic two-lobe buckling, which depended only on the elastic properties of the tube material and the dimensions of the tube; and (3) failure by a combination of (1) and (2) that is, by buckling taking place after some yielding of the tube material.

Stang, Ambrose H↗

Ultrasonic Guided-Wave-Scan System Used to Characterize C-Enhanced Silicon Carbide Composite During Creep- Rupture Tests

Ceramic matrix composites (CMCs) are being developed for advanced aerospace propulsion applications in order to save weight, improve reuse capability, and increase performance. However, mechanical and environmental loads applied to CMCs can cause degradation in the form of discrete flaws and distributed microdamage that can play a significant role in reducing desirable physical properties. Categories of microdamage include fiber/matrix debonding (interface failure), matrix microcracking, fiber fracture and buckling, oxidation, and second-phase formation. Distributed microdamage in CMCs has proven difficult to characterize nondestructively because of the complex microstructure and macrostructure of these materials, and a recent study regarding the durability of a ceramic matrix composite discussed the requirement for improved nondestructive evaluation (NDE) methods for monitoring degradation in these materials.

Roth, Don J.↗

Sensor Selection and Data Validation for Reliable Integrated System Health Management

For new access to space systems with challenging mission requirements, effective implementation of integrated system health management (ISHM) must be available early in the program to support the design of systems that are safe, reliable, highly autonomous. Early ISHM availability is also needed to promote design for affordable operations; increased knowledge of functional health provided by ISHM supports construction of more efficient operations infrastructure. Lack of early ISHM inclusion in the system design process could result in retrofitting health management systems to augment and expand operational and safety requirements; thereby increasing program cost and risk due to increased instrumentation and computational complexity. Having the right sensors generating the required data to perform condition assessment, such as fault detection and isolation, with a high degree of confidence is critical to reliable operation of ISHM. Also, the data being generated by the sensors needs to be qualified to ensure that the assessments made by the ISHM is not based on faulty data. NASA Glenn Research Center has been developing technologies for sensor selection and data validation as part of the FDDR (Fault Detection, Diagnosis, and Response) element of the Upper Stage project of the Ares 1 launch vehicle development. This presentation will provide an overview of the GRC approach to sensor selection and data quality validation and will present recent results from applications that are representative of the complexity of propulsion systems for access to space vehicles. A brief overview of the sensor selection and data quality validation approaches is provided below. The NASA GRC developed Systematic Sensor Selection Strategy (S4) is a model-based procedure for systematically and quantitatively selecting an optimal sensor suite to provide overall health assessment of a host system. S4 can be logically partitioned into three major subdivisions: the knowledge base, the down-select iteration, and the final selection analysis. The knowledge base required for productive use of S4 consists of system design information and heritage experience together with a focus on components with health implications. The sensor suite down-selection is an iterative process for identifying a group of sensors that provide good fault detection and isolation for targeted fault scenarios. In the final selection analysis, a statistical evaluation algorithm provides the final robustness test for each down-selected sensor suite. NASA GRC has developed an approach to sensor data qualification that applies empirical relationships, threshold detection techniques, and Bayesian belief theory to a network of sensors related by physics (i.e., analytical redundancy) in order to identify the failure of a given sensor within the network. This data quality validation approach extends the state-of-the-art, from red-lines and reasonableness checks that flag a sensor after it fails, to include analytical redundancy-based methods that can identify a sensor in the process of failing. The focus of this effort is on understanding the proper application of analytical redundancy-based data qualification methods for onboard use in monitoring Upper Stage sensors.

Garg, Sanjay↗

Stability Enhancement of Polymeric Sensing Films Using Fillers

Experiments have shown the stability enhancement of polymeric sensing films on mixing the polymer with colloidal filler particles (submicron-sized) of carbon black, silver, titanium dioxide, and fumed silicon dioxide. The polymer films are candidates for potential use as sensing media in micro/nano chemical sensor devices. The need for stability enhancement of polymer sensing films arises because such films have been found to exhibit unpredictable changes in sensing activity over time, which could result in a possible failure of the sensor device. The changes in the physical properties of a polymer sensing film caused by the sorption of a target molecule can be measured by any of several established transduction techniques: electrochemical, optical, calorimetric, or piezoelectric, for example. The transduction technique used in the current polymer stability experiments is based on piezoelectric principles using a quartz-crystal microbalance (QCM). The surface of the QCM is coated with the polymer, and the mass uptake by the polymer film causes a change in the oscillating frequency of the quartz crystal. The polymer used for the current study is ethyl cellulose. The polymer/ polymer composite solutions were prepared in 1,3 dioxolane solvent. The filler concentration was fixed at 10 weight percent for the composites. The polymer or polymer composite solutions were cast on the quartz crystal having a fundamental frequency of about 6 MHz. The coated crystal was subjected to a multistage drying process to remove all measurable traces of the solvent. In each experiment, the frequency of oscillation was measured while the QCM was exposed to clean, dry, flowing air for about 30 minutes, then to air containing a known concentration of isopropanol for about 30 minutes, then again to clean dry air for about 30 minutes, and so forth. This cycle of measurements for varying isopropanol concentrations was repeated at intervals for several months. The figure depicts some of the sensing film stability results for ethyl cellulose polymer, ethyl cellulose-carbon black, and ethyl cellulose-silicon dioxide composite systems. An ethyl cellulose film exhibited a marked decline in response in the first few months of study and settled to a steady average response after about four months. However, response varied widely around the average response for ethyl cellulose film. In contrast, ethyl cellulose- carbon black and ethyl cellulose-silicon dioxide composites also declined in the early months, but showed more repeatable sensing film activity after the initial decline. Similar trends were observed in experiments for ethyl cellulose-titanium dioxide and ethyl cellulose-silver composites.

Lin, Brian↗

CO2 Removal Onboard the International Space Station – Material Selection and System Design

The previous three years of efforts have focused on the study of the sorbent materials available for use in a 4-bed molecular sieve system. The accumulation of knowledge has been invaluable for further decisions and for reflecting on the conclusions of past decisions. The goal of the next system is perfect uptime for nearly 20,000 hours of operation, but no complex life support system has yet reached this lofty goal. In addition to reliability, CO2 removal performance improvements have been intensively studied. The achievements toward this end include highly detailed isotherm measurements which drive system simulations as well as testing physical design improvements. Looking back on the successes and failures of past systems, correlating tests with long-duration data, and carefully projecting the future are all needed for the success of the next system. This work intends to reveal the path we have taken and illuminate the steps to come for CO2 removal life support with the 4BCO2 flight demonstration.

Cmarik, Gregory E.↗

Verification and Validation of Progressive Damage and Failure Analysis Methods for Intralaminar Failure Modes in Thermoplastic Composites

Current progressive damage and failure analysis (PDFA) methods were developed around thermoset material systems and their physical behavior. However, the applicability of these analysis methods has not been evaluated for use in modeling thermoplastic material systems. As part of the Hi-Rate Composite Aircraft Manufacturing (HiCAM) Project sponsored by NASA, intralaminar failure characterization was completed on a thermoplastic material system, AS4D/PEKK-FC, with off-axis tension (OAT) and off-axis compression (OAC) testing. The experiments were able to capture matrix non-linear shear behavior and the failure envelope of the material system. Two PDFA methods, LS-DYNA MAT299 and NASA’s CompDam-DGD, were then employed to simulate individual coupon behavior and simulation results were compared to published verification and validation guidelines from the CMH-17 crashworthiness working group. The results found that the two modeling methods provided suitable representation of material behavior of thermoplastics.

PDFA↗

Verification and Validation of Progressive Damage and Failure Analysis Methods for Intralaminar Failure Modes in Thermoplastic Composites

Current progressive damage and failure analysis (PDFA) methods were developed around thermoset material systems and their physical behavior. However, the applicability of these analysis methods has not been evaluated for use in modeling thermoplastic material systems. As part of the Hi-Rate Composite Aircraft Manufacturing (HiCAM) Project sponsored by NASA, intralaminar failure characterization was completed on a thermoplastic material system, AS4D/PEKK-FC, with off-axis tension (OAT) and off-axis compression (OAC) testing. The experiments were able to capture matrix non-linear shear behavior and the failure envelope of the material system. Two PDFA methods, LS-DYNA MAT299 and NASA’s CompDam-DGD, were then employed to simulate individual coupon behavior and simulation results were compared to published verification and validation guidelines from the CMH-17 crashworthiness working group. The results found that the two modeling methods provided suitable representation of material behavior of thermoplastics.

PDFA↗

A Fluid Solver for Studying Torsional Galloping in Solar-Tracking PV Panel Arrays

Solar-tracking photovoltaic arrays are susceptible to aeroelastic fluttering during high-wind events. This dynamic fluttering behavior can grow in amplitude until the panels enter an unstable mode known as torsional galloping which can lead to panel failure or total array destruction. To better understand the physics of the torsional galloping phenomenon, and to inform the discussion around panel design and recommended panel stow positions during high wind events, a fluid-structure interaction solver composed of a simulated atmospheric boundary layer with simplified panel structural responses was designed. The simulation choices and features of this solver were informed by the geometry and physical properties of an experimental panel array known to exhibit torsional galloping behavior during hind-wind events. These simulations revealed that the torsional galloping instability is driven by a combination of cyclic vortex shedding from the sun-facing side of the panel and the elastic properties of the torque tube linking the panel assemblies. Testing different stow angles across a range of wind speeds indicates that panels are generally more stable when stowed at negative angles where the leading edge is closer to the ground, hypothesized to be due to ground-blocking effects.

41 EE - Solar Energy Technologies Office (EE-4S)↗