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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.

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35 records · Page 2

Addressing the Real-World Challenges in the Development of Propulsion IVHM Technology Experiment (PITEX)

The Propulsion IVHM Technology Experiment (PITEX) has been an on-going research effort conducted over several years. PITEX has developed and applied a model-based diagnostic system for the main propulsion system of the X-34 reusable launch vehicle, a space-launch technology demonstrator. The application was simulation-based using detailed models of the propulsion subsystem to generate nominal and failure scenarios during captive carry, which is the most safety-critical portion of the X-34 flight. Since no system-level testing of the X-34 Main Propulsion System (MPS) was performed, these simulated data were used to verify and validate the software system. Advanced diagnostic and signal processing algorithms were developed and tested in real-time on flight-like hardware. In an attempt to expose potential performance problems, these PITEX algorithms were subject to numerous real-world effects in the simulated data including noise, sensor resolution, command/valve talkback information, and nominal build variations. The current research has demonstrated the potential benefits of model-based diagnostics, defined the performance metrics required to evaluate the diagnostic system, and studied the impact of real-world challenges encountered when monitoring propulsion subsystems.

Maul, William A.↗

Propulsion IVHM Technology Experiment

The Propulsion IVHM Technology Experiment (PITEX) successfully demonstrated real-time fault detection and isolation of a virtual reusable launch vehicle (RLV) main propulsion system (MPS). Specifically, the PITEX research project developed and applied a model-based diagnostic system for the MPS of the X-34 RLV, a space-launch technology demonstrator. The demonstration was simulation-based using detailed models of the propulsion subsystem to generate nominal and failure scenarios during captive carry, which is the most safety-critical portion of the X-34 flight. Since no system-level testing of the X-34 Main Propulsion System (MPS) was performed, these simulated data were used to verify and validate the software system. Advanced diagnostic and signal processing algorithms were developed and tested in real time on flight-like hardware. In an attempt to expose potential performance problems, the PITEX diagnostic system was subjected to numerous realistic effects in the simulated data including noise, sensor resolution, command/valve talkback information, and nominal build variations. In all cases, the PITEX system performed as required. The research demonstrated potential benefits of model-based diagnostics, defined performance metrics required to evaluate the diagnostic system, and studied the impact of real-world challenges encountered when monitoring propulsion subsystems.

Chicatelli, Amy K.↗

Verifying Diagnostic Software

Livingstone PathFinder (LPF) is a simulation-based computer program for verifying autonomous diagnostic software. LPF is designed especially to be applied to NASA s Livingstone computer program, which implements a qualitative-model-based algorithm that diagnoses faults in a complex automated system (e.g., an exploratory robot, spacecraft, or aircraft). LPF forms a software test bed containing a Livingstone diagnosis engine, embedded in a simulated operating environment consisting of a simulator of the system to be diagnosed by Livingstone and a driver program that issues commands and faults according to a nondeterministic scenario provided by the user. LPF runs the test bed through all executions allowed by the scenario, checking for various selectable error conditions after each step. All components of the test bed are instrumented, so that execution can be single-stepped both backward and forward. The architecture of LPF is modular and includes generic interfaces to facilitate substitution of alternative versions of its different parts. Altogether, LPF provides a flexible, extensible framework for simulation-based analysis of diagnostic software; these characteristics also render it amenable to application to diagnostic programs other than Livingstone.

Lindsey, Tony↗

CASPEr: an Approach to Characterize the Performance of Onboard Airplane Energy State and Automation Mode Prediction Functions

The Commercial Aviation Safety Team (CAST) has identified a set of safety enhancements to mitigate the risks of loss of control in-flight (LOCI) accidents and incidents involving commercial transport airplanes. In support of this, NASA has been developing technologies intended to enhance flight crew awareness of airplane systems, attitude, and energy state. This report describes preliminary ideas for a methodology to assess the goodness of onboard airplane energy state and automation mode prediction functions. The methodology is intended to contribute to the goal of moving these prediction technologies to the readiness level required for transition to industry and reduce the technology certification risks. In addition, this report describes a simulation-based approach named CASPEr (Characterization of Airplane State Prediction Error) to characterize the performance of these predictive functions over a wide range of operational conditions. The first exploratory version of this approach is described. The bulk of the report documents the initial results of tests to characterize the performance of an airplane trajectory prediction function. Future reports will give additional performance characterization results for this function and a complete description of the proposed methodology to assess such functions.

Torres-Pomales, Wilfredo↗

Stochastic Verification by Analysis for Autonomous Systems Management Architecture (ASMA)

The Gateway Vehicle Systems Manager (VSM) is the top-level of a distributed, hierarchical software control system. VSM is data-driven and will make decisions related to mission, fault, resource management and vehicle control. These attributes combined with a high degree of autonomy make it susceptible to emergent behavior. In order to achieve the high level of confidence needed in this critical system, the VSM team has developed a multifaceted verification strategy employing traditional verification techniques, simulation, model checking, and runtime verification. Individual algorithms are verified using conventional testing and model checking using assume-guarantee contracts. A discrete event-based simulation approach is being developed to verify timelines. This presentation describes an enhancement to the verification approach using analysis to enhance system robustness by detecting and resolving the potential for emergent behavior. The verification by analysis employs a Software in the Loop (SITL) environment with real flight software executing on emulated processors, simulations of vehicle subsystems, flight dynamics, and human inputs. Since the possible input space and configuration data set are too large for exhaustive testing, a Monte Carlo approach is used to cover feasible scenarios, augmented with corner cases and known higher-risk scenarios. A key problem in using Monte Carlo-based system verification is evaluating test results to ensure that system behavior is correct. The presentation describes the approach the VSM team uses to monitor behavior for compliance with predetermined boundaries and to identify anomalous behavior for further analysis. This presentation describes the multi-level systems approach to verification, and the simulation-based layer that covers the feasible state space: 1. Overview of the Gateway VSM 2. Special challenges due to heterogeneous, hierarchical architecture 3. Modeling and simulation environment using flight software and system simulations 4. Developing input sets to ensure state-space coverage 5. Developing model and data configuration sets to ensure model coverage 6. Interpreting results without predetermined outcomes 7. Lessons learned and future work

Verification and Validation↗

Estimation and enhancement of real-time software reliability through mutation analysis

A simulation-based technique for obtaining numerical estimates of the reliability of N-version, real-time software is presented. An extended stochastic Petri net is employed to represent the synchronization structure of N versions of the software, where dependencies among versions are modeled through correlated sampling of module execution times. Test results utilizing specifications for NASA's planetary lander control software indicate that mutation-based testing could hold greater potential for enhancing reliability than the desirable but perhaps unachievable goal of independence among N versions.

Geist, Robert↗

Discrete Event Simulation-Based Timeline Validation Using R2U2

The Gateway Vehicle Systems Manager (VSM), the top-level software control system in a distributed, hierarchical Autonomous System Management Architecture is, like most modern spacecraft software control systems, heavily data-driven. For example, schedules (timelines) will be developed on the ground and, due to the high degree of autonomy, contain complex procedures involving conditional branching, variable timing, and resource contention resolution. In order to verify that an uploaded timeline will function correctly, it is necessary to explore the feasible set of possible executions. While it is possible to test a timeline using a mission simulation, the complexity of the system and duration of a timeline limits the number of trials and therefore the test coverage. To address this problem, the VSM team is using a discrete event system model that can rapidly generate from a timeline sets of event sequences using Monte Carlo techniques. To achieve rapid and trustworthy checking of the event sequences, we use an offline version of the runtime model checking tool R2U2. This presentation describes the approach the VSM team is using to implement the discrete event simulation and evaluate event sequences using R2U2. The presentation will discuss: 1. Description of the timelines by VSM in the context of VSM operations 2. Expansion of a timeline into a sequence of atomic events 3. Adjustment, in the Monte Carlo environment, of an event sequence to account for uncertainty, external events, and failures 4. Definition of R2U2 input and mission-time linear temporal logic files 5. Generation and use of R2U2 verdict sequences 6. Lessons learned and future work

Verification↗

Adaptive Augmenting Control Flight Characterization Experiment on an F/A-18

This paper summarizes the Adaptive Augmenting Control (AAC) flight characterization experiments performed using an F/A-18 (TN 853). AAC was designed and developed specifically for launch vehicles, and is currently part of the baseline autopilot design for NASA's Space Launch System (SLS). The scope covered here includes a brief overview of the algorithm (covered in more detail elsewhere), motivation and benefits of flight testing, top-level SLS flight test objectives, applicability of the F/A-18 as a platform for testing a launch vehicle control design, test cases designed to fully vet the AAC algorithm, flight test results, and conclusions regarding the functionality of AAC. The AAC algorithm developed at Marshall Space Flight Center is a forward loop gain multiplicative adaptive algorithm that modifies the total attitude control system gain in response to sensed model errors or undesirable parasitic mode resonances. The AAC algorithm provides the capability to improve or decrease performance by balancing attitude tracking with the mitigation of parasitic dynamics, such as control-structure interaction or servo-actuator limit cycles. In the case of the latter, if unmodeled or mismodeled parasitic dynamics are present that would otherwise result in a closed-loop instability or near instability, the adaptive controller decreases the total loop gain to reduce the interaction between these dynamics and the controller. This is in contrast to traditional adaptive control logic, which focuses on improving performance by increasing gain. The computationally simple AAC attitude control algorithm has stability properties that are reconcilable in the context of classical frequency-domain criteria (i.e., gain and phase margin). The algorithm assumes that the baseline attitude control design is well-tuned for a nominal trajectory and is designed to adapt only when necessary. Furthermore, the adaptation is attracted to the nominal design and adapts only on an as-needed basis (see Figure 1). The MSFC algorithm design was formulated during the Constellation Program and reached a high maturity level during SLS through simulation-based development and internal and external analytical review. The AAC algorithm design has three summary-level objectives: (1) "Do no harm;" return to baseline control design when not needed, (2) Increase performance; respond to error in ability of vehicle to track command, and (3) Regain stability; respond to undesirable control-structure interaction or other parasitic dynamics. AAC has been successfully implemented as part of the Space Launch System baseline design, including extensive testing in high-fidelity 6-DOF simulations the details of which are described in [1]. The Dryden Flight Research Center's F/A-18 Full-Scale Advanced Systems Testbed (FAST) platform is used to conduct an algorithm flight characterization experiment intended to fully vet the aforementioned design objectives. FAST was specifically designed with this type of test program in mind. The onboard flight control system has full-authority experiment control of ten aerodynamic effectors and two throttles. It has production and research sensor inputs and pilot engage/disengage and real-time configuration of up to eight different experiments on a single flight. It has failure detection and automatic reversion to fail-safe mode. The F/A-18 aircraft has an experiment envelope cleared for full-authority control and maneuvering and exhibits characteristics for robust recovery from unusual attitudes and configurations aided by the presence of a qualified test pilot. The F/A-18 aircraft has relatively high mass and inertia with exceptional performance; the F/A-18 also has a large thrust-to-weight ratio, owing to its military heritage. This enables the simulation of a portion of the ascent trajectory with a high degree of dynamic similarity to a launch vehicle, and the research flight control system can simulate unstable longitudinal dynamics. Parasitic dynamics such as slosh and bending modes, as well as atmospheric disturbances, are being produced by the airframe via modification of bending filters and the use of secondary control surfaces, including leading and trailing edge flaps, symmetric ailerons, and symmetric rudders. The platform also has the ability to inject signals in flight to simulate structural mode resonances or other challenging dynamics. This platform also offers more test maneuvers and longer maneuver times than a single rocket or missile test, which provides ample opportunity to fully and repeatedly exercise all aspects of the algorithm. Prior to testing on an F/A-18, AAC was the only component of the SLS autopilot design that had not been flight tested. The testing described in this paper raises the Technology Readiness Level (TRL) early in the SLS Program and is able to demonstrate its capabilities and robustness in a flight environment.

VanZwieten, Tannen S.↗

The effects of a dynamic graphical model during simulation-based training of console operation skill

LOADER is a Windows-based simulation of a complex procedural task. The task requires subjects to execute long sequences of console-operation actions (e.g., button presses, switch actuations, dial rotations) to accomplish specific goals. The LOADER interface is a graphical computer-simulated console which controls railroad cars, tracks, and cranes in a fictitious railroad yard. We hypothesized that acquisition of LOADER performance skill would be supported by the representation of a dynamic graphical model linking console actions to goal and goal states in the 'railroad yard'. Twenty-nine subjects were randomly assigned to one of two treatments (i.e., dynamic model or no model). During training, both groups received identical text-based instruction in an instructional-window above the LOADER interface. One group, however, additionally saw a dynamic version of the bird's-eye view of the railroad yard. After training, both groups were tested under identical conditions. They were asked to perform the complete procedure without guidance and without access to either type of railroad yard representation. Results indicate that rather than becoming dependent on the animated rail yard model, subjects in the dynamic model condition apparently internalized the model, as evidenced by their performance after the model was removed.

Farquhar, John D.↗

Rapid Technology Assessment via Unified Deployment of Global Optical and Virtual Diagnostics

This paper discusses recent developments in rapid technology assessment resulting from an active collaboration between researchers at the Air Force Research Laboratory (AFRL) at Wright Patterson Air Force Base (WPAFB) and the NASA Langley Research Center (LaRC). This program targets the unified development and deployment of global measurement technologies coupled with a virtual diagnostic interface to enable the comparative evaluation of experimental and computational results. Continuing efforts focus on the development of seamless data translation methods to enable integration of data sets of disparate file format in a common platform. Results from a successful low-speed wind tunnel test at WPAFB in which global surface pressure distributions were acquired simultaneously with model deformation and geometry measurements are discussed and comparatively evaluated with numerical simulations. Intensity- and lifetime-based pressure-sensitive paint (PSP) and projection moire interferometry (PMI) results are presented within the context of rapid technology assessment to enable simulation-based R&D.

Jordan, Jeffrey D.↗

Adjustable Autonomy Testbed

The Adjustable Autonomy Testbed (AAT) is a simulation-based testbed located in the Intelligent Systems Laboratory in the Automation, Robotics and Simulation Division at NASA Johnson Space Center. The purpose of the testbed is to support evaluation and validation of prototypes of adjustable autonomous agent software for control and fault management for complex systems. The AA T project has developed prototype adjustable autonomous agent software and human interfaces for cooperative fault management. This software builds on current autonomous agent technology by altering the architecture, components and interfaces for effective teamwork between autonomous systems and human experts. Autonomous agents include a planner, flexible executive, low level control and deductive model-based fault isolation. Adjustable autonomy is intended to increase the flexibility and effectiveness of fault management with an autonomous system. The test domain for this work is control of advanced life support systems for habitats for planetary exploration. The CONFIG hybrid discrete event simulation environment provides flexible and dynamically reconfigurable models of the behavior of components and fluids in the life support systems. Both discrete event and continuous (discrete time) simulation are supported, and flows and pressures are computed globally. This provides fast dynamic simulations of interacting hardware systems in closed loops that can be reconfigured during operations scenarios, producing complex cascading effects of operations and failures. Current object-oriented model libraries support modeling of fluid systems, and models have been developed of physico-chemical and biological subsystems for processing advanced life support gases. In FY01, water recovery system models will be developed.

Malin, Jane T.↗

Range Process Simulation Tool

Range Process Simulation Tool (RPST) is a computer program that assists managers in rapidly predicting and quantitatively assessing the operational effects of proposed technological additions to, and/or upgrades of, complex facilities and engineering systems such as the Eastern Test Range. Originally designed for application to space transportation systems, RPST is also suitable for assessing effects of proposed changes in industrial facilities and large organizations. RPST follows a model-based approach that includes finite-capacity schedule analysis and discrete-event process simulation. A component-based, scalable, open architecture makes RPST easily and rapidly tailorable for diverse applications. Specific RPST functions include: (1) definition of analysis objectives and performance metrics; (2) selection of process templates from a processtemplate library; (3) configuration of process models for detailed simulation and schedule analysis; (4) design of operations- analysis experiments; (5) schedule and simulation-based process analysis; and (6) optimization of performance by use of genetic algorithms and simulated annealing. The main benefits afforded by RPST are provision of information that can be used to reduce costs of operation and maintenance, and the capability for affordable, accurate, and reliable prediction and exploration of the consequences of many alternative proposed decisions.

Phillips, Dave↗

Simulation-Based Airframe Noise Prediction of a Full-Scale, Full Aircraft

A previously validated computational approach applied to an 18%-scale, semi-span Gulfstream aircraft model was extended to the full-scale, full-span aircraft in the present investigation. The full-scale flap and main landing gear geometries used in the simulations are nearly identical to those flown on the actual aircraft. The lattice Boltzmann solver PowerFLOW® was used to perform time-accurate predictions of the flow field associated with this aircraft. The simulations were performed at a Mach number of 0.2 with the flap deflected 39 deg. and main landing gear deployed (landing configuration). Special attention was paid to the accurate prediction of major sources of flap tip and main landing gear noise. Computed farfield noise spectra for three selected baseline configurations (flap deflected 39 deg. with and without main gear extended, and flap deflected 0 deg. with gear deployed) are presented. The flap brackets are shown to be important contributors to the farfield noise spectra in the mid- to high-frequency range. Simulated farfield noise spectra for the baseline configurations, obtained using a Ffowcs Williams and Hawkings acoustic analogy approach, were found to be in close agreement with acoustic measurements acquired during the 2006 NASA-Gulfstream joint flight test of the same aircraft.

Khorrami, Mehdi R.↗

Simulation-Based Assessment of a Full-Scale Installed Quiet Landing Gear

Full-scale simulations of a Gulfstream G-III aircraft, performed in support of the NASA Acoustic Research Measurements flights, are presented to complement results discussed in earlier studies. The flow solver employed in those studies, Dassault Systèmes’ lattice Boltzmann PowerFLOW®, was also used during this investigation to conduct time-dependent simulations of the entire aircraft in landing configuration with a fully dressed landing gear. The high-fidelity simulations, performed at a Mach number of 0.23 and a Reynolds number of 10.5 × 106 based on mean aerodynamic chord, captured all relevant airframe noise sources. The computations were used to assess the aeroacoustic performance of the main landing gear, with and without noise reduction fairings installed, of a G-III aircraft equipped with Adaptive Compliant Trailing Edge technology and conventional Fowler flaps. To facilitate comparison of predicted noise signatures with effective perceived noise levels obtained from flight test measurements, the “as-flown” nose landing gear geometry, missing in our earlier studies, was added to the simulated G-III aircraft configurations. The high fidelity, synthetic data were post-processed using a Ffowcs-Williams and Hawkings integral approach to estimate farfield acoustic behavior, with pressures on the model solid surface or pressure and velocity components on a permeable surface enveloping the acoustic near field used as input.

Duda, Benjamin↗

Application Table: A Bridge Connecting the Designing “With-The-Material” and “The-Material” Paradigms

Over the last few decades, advances in high-performance computing, new material characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. In 2016 NASA sponsored a 2040 Vision study (which appeared in 2018) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. The study envisions a cyber-physical-social ecosystem comprised of experimentally verified and validated (V & V) computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of “fit-for-purpose” materials, components, and systems. Consequently, the development of a robust information management system that incorporates (across the full life cycle) both experimental (real data) and virtual data resulting from the application of various simulation tools (at single or multiple length scales), therefore enabling the virtual design and optimization of materials throughout their processing – internal structure – property – performance envelope, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality, and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. This is particularly true when attempting to merge ICME practices with recent additive manufacturing technology which will enable production of the resulting 2040 Vision material and structural designs. At NASA Glenn Research Center we are exploring the future of material science through the use of novel characterization methodologies, high performance computing, and recently an emphasis on integrated computational materials engineering (ICME). Herein, recent efforts to incorporate an Application Table within NASA Glenn Research Center’s ICME Granta MI database is presented. The goal is to provide a place where material and structural application information/requirements can be linked so as to marry the “design the-material” and the “design-with-material” paradigms and thereby enable application-driven design and optimization of materials and structures by providing a central location that links material processing at various length scales to the application’s performance requirements. This paper discusses the specifics of this Application Table as well as best practices and key principles for the development of a robust materials information management system to enable the 2040 Vision integrated materials and structures ecosystem. Furthermore, it presents the intended role of the Application Table in the future of ICME design of “fit-for-purpose” materials, showing the need for a well-established framework that can successfully bridge the gap between the design “the material” and design “with-the-material” paradigms.

Materials↗

Application Table: A Bridge Connecting the Designing “With-the-Material” and “the-Material”

Over the last few decades, advances in high-performance computing, new material characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. In 2016 NASA sponsored a 2040 Vision study (which appeared in 2018) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. The study envisions a cyber-physical-social ecosystem comprised of experimentally verified and validated (V & V) computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of “fit-for-purpose” materials, components, and systems. Consequently, the development of a robust information management system that incorporates (across the full life cycle) both experimental (real data) and virtual data resulting from the application of various simulation tools (at single or multiple length scales), therefore enabling the virtual design and optimization of materials throughout their processing – internal structure – property – performance envelope, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality, and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. This is particularly true when attempting to merge ICME practices with recent additive manufacturing technology which will enable production of the resulting 2040 Vision material and structural designs. At NASA Glenn Research Center we are exploring the future of material science through the use of novel characterization methodologies, high performance computing, and recently an emphasis on integrated computational materials engineering (ICME). Herein, recent efforts to incorporate an Application Table within NASA Glenn Research Center’s ICME Granta MI database is presented. The goal is to provide a place where material and structural application information/requirements can be linked so as to marry the “design the-material” and the “design-with-material” paradigms and thereby enable application-driven design and optimization of materials and structures by providing a central location that links material processing at various length scales to the application’s performance requirements. This paper discusses the specifics of this Application Table as well as best practices and key principles for the development of a robust materials information management system to enable the 2040 Vision integrated materials and structures ecosystem. Furthermore, it presents the intended role of the Application Table in the future of ICME design of “fit-for-purpose” materials, showing the need for a well-established framework that can successfully bridge the gap between the design “the material” and design “with-the-material” paradigms.

Materials↗

Multiscale Prediction of Yarn Pullout Failure Mode in Unreinforced Textile Fabrics

Unreinforced woven fabrics have been implemented in a variety of high performance applications, including body armor, deployable structures, and as the reinforcement material in composites. Multiscale modeling techniques have significantly improved the capabilities of simulation-based tools to capture fabric mechanics efficiently and accurately, but often lack in their prediction of failure and require pairing with finite element analysis (FEA) software, limiting their application to the design of ‘fit-for-purpose’ materials. NASA’s Multiscale Analysis Tool (NASMAT) is a standalone multiscale program that has been traditionally used in the analysis of reinforced composites materials. More recently, it has been amended to simulate unreinforced fabric behavior by allowing the geometric state of the tows to change with applied loading due to the lack of a reinforcement material, such as the matrix seen in composites. Previous work has shown the ability of NASMAT to capture nonlinear macroscale behavior by predicting geometric changes in the state of each subcell as a function of the applied loading and allowing each subcell in the analysis to rotate according to these predicted changes, as well as predict nonlinear behavior due to the fiber breakage failure mode. In this work, the capability of predicting the onset and propagation of failure in plain woven fabrics in NASMAT is presented for the yarn pullout failure mode, which occurs when a fabric is loaded at an off-axis angle relative to the warp of weft tow direction. Yarn pullout behavior is initiated by determining the applied load in which the shear resistance of the contact area between yarn families is overcome. When failure is initiated, yarn pullout is determined to have occurred when the applied displacement, calculated from global strain, exceeds the deformed position of a given contact points between yarn families, determined from pin-joint kinematics. Contact points where pullout has occurred contribute to a global damage parameter used to modify the homogenized stiffness of the fabric, resulting in nonlinear behavior observed at the macroscale. The off-axis loading behavior and yarn pullout failure theory have been developed and implemented into NASMAT such that users can simulate off-axis tensile behavior of fabrics in a single, standalone multiscale tool. Simulations are compared to uniaxial tensile tests at various off-axis angles to demonstrate the capability of the tool in its prediction of both the onset of failure at each off-axis angles and the stress-strain behavior as failure progresses.

Materials↗