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A comprehensive plasticity and fracture model was built for metal sheets with application to metal sheet forming and vehicle crash simulations. The combined Bai-Wierzbicki (BW [1]) and CPB06ex2 [2] (or Yld2000-2D [3]) anisotropic plasticity model was further extended to consider elevated temperature effects in additional to the effect of multiaxial stress states. A fully modularized framework was established to combine isotropic, kinematic, and cross hardening behaviors under non-linear loading conditions. The all strain based modified Mohr-Coulomb (eMMC) fracture model was used to consider material anisotropy and nonlinear strain path. The model has been implemented into Abaqus/Explicit as a user material subroutine (VUMAT). Test results on advanced high strength steels, aluminum alloy sheets and magnesium alloy sheets are used to validate the modeling and testing methodologies. Very good correlation was observed between experimental and simulation results.

This paper features a distributed environment and the steps taken to incorporate the Virtual Range model into the Virtual Test Bed (VTB) infrastructure. The VTB is a prototype of a virtual engineering environment to study operations of current and future space vehicles, spaceports, and ranges. The High-Level Architecture (HLA) is the main environment. The VTB/HLA implementation described here represents different systems that interact in the simulation of a Space Shuttle liftoff. An example implementation displays the collaboration of a simplified version of the Space Shuttle Simulation Model and a simulation of the Launch Scrub Evaluation Model.

This paper describes the development of a distributed environment for spaceport simulation modeling. This distributed environment is the result of the applications of the High-Level Architecture (HLA) and integration frameworks based on software agents and XML. This distributed environment is called the Virtual Test Bed (VTB). A distributed environment is needed due to the nature of the different models needed to represent a spaceport. This paper provides two case studies: one related to the translation of a model from its native environment and the other one related to the integration of real-time weather.

The future of human exploration in the solar system is contingent on the ability to exploit resources in-situ to produce mission consumables. Specifically, it has become clear that the success of a manned mission to Mars will likely depend on fuel components created on the Martian surface. While several architectures for an unmanned fuel production surface facility on Mars exist in theory, a simulation of the performance and operation of these architectures has not been created. In this paper, the framework describing a simulation of one such architecture is defined. Within this architecture, each component of the base is implemented as a state machine, with the ability to communicate with other base elements as well as a supervisor. An environment supervisor is also created which governs low level aspects of the simulation such as movement and resource distribution, in addition to higher-level aspects such as location selection with respect to operations specific behavior.

As the cost and complexity of modern aircraft systems increases, emphasis has been placed on model-based design as a means for reducing development cost and optimizing performance. To facilitate this, an appropriate modeling environment is required that allows developers to rapidly explore a wider design space than can cost effectively be considered through hardware construction and testing. This wide design space can then yield solutions that are far more energy efficient than previous generation designs. In addition, non-intuitive cross-coupled subsystem behavior can also be explored to ensure integrated system stability prior to hardware fabrication and testing. In recent years, optimization of control strategies between coupled subsystems has necessitated the understanding of the integrated system dynamics.

In this paper, we address the thermal management issues which limit the lifespan, specific power and overall efficiency of an air-cooled rotary Wankel engine used in Unmanned Air Vehicles (UAVs). Our goal is to eliminate the hot spots and reduce the temperature gradients in the engine housing and side plates by aggressive heat spreading using heat pipes. We demonstrate by simulation that, for a specific power requirement, with heat spreading and more effective heat dissipation, thermal stress and distortion can be significantly reduced, even with air cooling. The maximum temperature drop was substantial, from 231°C to 129°C. The temperature difference (measure of temperature uniformity) decreased by 8.8 times (from 159°C to 18°C) for a typical UAV engine. Our heat spreaders would not change the frontal area of the engine and should have a negligible impact on the installed weight of the propulsion assembly.

Operator training using a weapon in a real-world environment is risky, expensive, time-consuming, and restricted to the given environment. In addition, governments are under intense scrutiny to provide security, yet they must also strive for efficiency and reduce spending. In other words, they must do more with less. Virtual simulation, is usually employed to solve these limitations. As the operator is trained to maximize weapon effectiveness, the effectiveness-focused training can be completed in an economical manner. Unfortunately, the training is completed in limited scenarios without objective levels of training factors for an individual operator to optimize the weapon effectiveness. Thus, the training will not be effective. For overcoming this problem, we suggest a methodology on guiding effectiveness-focused training of the weapon operator through usability assessments, big data, and Virtual and Constructive (VC) simulations.

This paper describes a model-based approach to diagnosing electrical faults in electrical power systems. Until recently, model-based reasoning has only been applied to physical systems with static, persistent states, and with parts whose behavior can be expressed combinatorially, such as digital circuits. Our research is one of a handful of recent efforts to apply model-based reasoning to more complex systems, those whose behavior is difficult or impossible to express combinatorially, and whose states change continuously over time. The chosen approach to representation is loosely based on the idea of the equation network proposed in [6]. This requires a more complex component and behavior model than for simpler physical devices. The resulting system is being tested on fault data from the SSM/PMAD power system breadboard being developed at NASA-MSFC [9].

A fully modularized framework was established to combine isotropic, kinematic, and cross hardening behaviors under non-monotonic loading conditions for advanced high strength steels. Experiments under the following types of non-proportional loading conditions were conducted, 1) uniaxial tension-compression-tension/compression-tension-compression full cycle reversal loading, 2) uniaxial reversal loading with multiple cycles, and 3) reversal shear. The calibrated new model is decoupled between isotropic and kinematic hardening behaviors, and independent on both anisotropic yield criterion and fracture model. Nine materials were calibrated using the model, include: DP590, DP600, DP780, TRIP780, DP980LY, QP980, AK Steel DP980, TBF1180, and AK Steel DP1180. Good correlation was observed between experimental and modeled results.

The Air Force Research Laboratory Deployment and Sustainment Division (AFRL/HES), in coordination with Arthur D. Little, Inc., has undertaken a system-of-systems approach to defining and designing aerospace ground equipment (AGE). This method is usually used to take advantage of the open architecture nature of ne and developing electronics through modular design. This paper discusses how we applied it across the electronic, mechanical, and structural aspects of AGE to research and develop a new concept to meet the burgeoning needs of the 21st century Air Force.

As part of the DoD/NASA Lithium-Ion and More-Electric Aircraft (MEA) development programs, in-house life-testing and performance characterization of lithium-ion batteries of sizes 1-20 amp-hours (Ah) were performed. Using AC impedance spectroscopy, the impedance behavior of lithium-ion cells with respect to temperature, cycle number, electrode, and state-of-charge was determined. Cell impedance is dominated by the positive (cathode) electrode, increases linearly with cycle number, and exponentially increases with decreasing temperature. From cell performance testing, we have seen the cell behavior is extremely sensitive to the ambient temperature. Preliminary battery performance results as well as AC impedance and life cycle test results are presented below.

This paper describes the development, operation and testing of an across-gimbal ambient thermal transport system (GATTS) for carrying cryocooler waste heat across a 2-axis gimbal. The principal application for the system is space-based remote sensing spacecraft with gimbaled cryogenics optics and/or infrared sensors. GATTS uses loop heat pipe (LHP) technology with ammonia as the working fluid and small diameter stainless steel tubing to transport 100–275 W across a two-axis gimbal. The tubing is coiled around each gimbal axis to provide flexibility (less than 0.68 N-m [6 lbf-in] of tubing-induced torque per axis) and fatigue life. Stepper motors are implemented to conduct life cycling and to assess the impact of motion on thermal performance. An LHP conductance of approximately 7.5 W/C was demonstrated at 200 W, with and without gimbal motion. At the time this paper was written, the gimbal had successfully completed over 500,000 cycles of operation with no performance degradation.

As technology for both military and civilian aviation systems mature into a new era, techniques to test and evaluate these systems have become of great interest. To achieve a general understanding as well as save time and cost, the use of computer modeling and simulation for component, subsystem or integrated system testing has become a central part of technology development programs. However, the evolving complexity of the systems being modeled leads to a tremendous increase in the complexity of the developed models. To gain confidence in these models there is a need to evaluate the risk in using those models for decision making. Statistical model validation techniques are used to assess the risk of using a given model in decision making exercises. In this paper, we formulate a transient model validation challenge problem for an air cycle machine (ACM) and present a hardware test bench used to generate experimental data relevant to the model.

Complex aerospace engineering systems require innovative methods for performance monitoring and anomaly detection. The interface of a real-time data stream to a system for analysis, pattern recognition, and anomaly detection can require distributed system architectures and sophisticated custom programming. This paper presents a case study of a simplified interface between Programmable Logic Controller (PLC) real-time data output, signal processing, cloud computing, and tablet systems. The discussed approach consists of three parts: First, the connectivity of real-time data from PLCs to the signal processing algorithms, using standard communication technologies. Second, the interface of legacy routines, such as NASA's Inductive Monitoring System (IMS), with a hybrid signal processing system. Third, the connectivity and interaction of the signal processing system with a wireless and distributed tablet, (iPhone/iPad) in a hybrid system configuration using cloud computing.

The modeling and simulation pyramid in defense states it clearly: Multi-Level modeling and simulation are required. Models and simulations are often classified by the US Department of Defense into four levels—campaign, mission, engagement, and engineering. Campaign simulation models are applied for evaluation; mission-level simulations to experiment with the integration of several macro agents; engagement simulations in engineered systems development; and engineering-level simulation models with a solid foundation in structural physics and components. Models operating at one level must be able to interact with models at another level. Therefore, the cure (“silver bullet”) is very clear: a comprehensive framework for Multiple Resolution Modeling (MRM) is needed. In this paper, we discuss our research about how to construct MRM environments.

As an engineering approach of balanced complexity and accuracy, the Generalized Incremental Stress-State dependent damage Model (GISSMO) in LS-DYNA® has now been widely adopted by the automotive industry to predict metallic materials’ fracture occurrences in both forming and crashworthiness simulations. Calibration of the nominal GISSMO is typically based on material characterization data along a certain representative material orientation. Nevertheless, many rolled or extruded metallic materials, such as advanced high-strength steel (AHSS) sheets, exhibit accentuated anisotropic fracture behavior, even though, notably, some of these materials show comparatively weak anisotropic plasticity in the meantime. Accordingly, in this work, the deformation and fracture behavior of a selected AHSS grade, Q&P980 steel, was first characterized based on a series of mechanical experiments under simple shear, uniaxial tension, plane strain, and equi-biaxial tension conditions.

Multi-Resolution Modeling (MRM) is one of the key technologies for building complex and large-scale simulations using legacy simulators. MRM has been developed continuously, especially in military fields. MRM plays a crucial role to describe the battlefield and gathering the desired information efficiently by linking various levels of resolution. The simulation models interact across different local and/or distance area networks using the High Level Architecture (HLA) regardless of their operating systems and hardware. The HLA is a standard architecture developed by the US Department of Defense (DoD) and is meant to create interoperability among different types of simulators. Therefore, MRM implementations are very dependent on Interoperability and Composability. This paper summarizes the definition of MRM-related terminology and proposes a basic form of MRM system using Commercial Off-The-Shelf (COTS) simulators and HLA.

The traditional acquisition and development cycles of a weapon system by government agencies goes through multiple stages throughout the life cycle of the product. Over the last few decades, many of the United States military equipment had experienced acquisition cost growth. Many studies by the Department of Defense indicates that the cost growth is a result of multiple factors including the development and manufacturing stages of the product. Organizations with multiple operation sites that goes across multiple states or even countries and continents are finding it increasingly difficult to share informational databases to ensure the corporate synergy between multiple sites or divisions. For such organizations, there exist the need to synchronize the operations and have standard and common database where everything is stored and equally accessed by different sites. Digital transformation sounds real exotic and futuristic and promise to reduce operation costs of big organizations.

Modern military engines desire both the fuel efficiency of high-bypass turbofans and the high specific thrust of a low-bypass turbofan. Using traditional engine architectures, performance and efficiency are in conflict, so an engine is usually designed to best meet requirements for its primary mission. While the concept of a variable cycle engine is not new, recent advances in engine architecture technology suggest that adding a second bypass stream to a traditional turbofan can provide significant benefits. This “third stream” (the core flow being the primary stream and the inner bypass being the second stream) airflow can be independently modulated so that engine airflow demand can be matched with the available inlet flow at a variety of operating points, thereby reducing spillage drag. Additionally, the third stream air provides a valuable heat sink for cooling turbine cooling air or dissipating other aircraft heat loads.

Connected and Autonomous Vehicles (CAV) rely on information obtained from sensors and communication to make decisions. In a Cooperative Vehicle Safety (CVS) system, information from remote vehicles (RV) is available at the host vehicle (HV) through the wireless network. Safety applications such as crash warning algorithms use this information to estimate the RV and HV states. However, this information is uncertain and sparse due to communication losses, limitations of communication protocols in high congestion scenarios, and perception errors caused by sensor limitations. In this paper we present a novel approach to improve the robustness of the CVS systems, by proposing an architecture that divide application and information/perception subsystems and a novel prediction method based on non-parametric Bayesian inference to mitigate the detrimental effect of data loss on the performance of safety applications.