Search Results

Aerospace projects live a long time. Around the turn of the century, NASA first began to discuss multi-decadal projects with respect to the tools, methods, infrastructure and culture necessary to successfully establish outposts and bases both on the Moon as well as in adjacent space. Pilot projects were completed, capabilities developed and solutions were shared across the Agency. A decade later the Mars discussion was multi-generational with planning milestones 50 years in the future. The 1970’s Requirements Document, or the 1990’s System Model are nowhere near suitable for planning, development, integration and operations of multi-national, highly complex, incredibly expensive development efforts planned to outlast not only the careers of the developers but that of their children as well. Simulation in the different forms has become very important for this multi-decadal projects. The challenge will be to device ways to create formats and views which can stand time.

The National Aeronautics and Space Administration’s (NASA) current objectives include expanding space exploration and planning a manned expedition to Mars. In order to meet the latter objective, it is imperative that humans generate their own products by harnessing space resources, a process referred to as In-Situ Resource Utilization (ISRU). ISRU will enable NASA to reduce both payload mass and mission cost by reducing the number of consumables required to be launched from Earth. The discrete-event simulation discussed focuses primarily on one ISRU system, the production of fuel for a return trip to Earth by utilizing Mar’s atmosphere and regolith. This ISRU system primarily uses autonomous rovers for exploration, excavation, processing of Mar’s regolith to produce fuel, and disposal of the processed regolith. This study explores individual rover and component requirements including rover speeds, travel distances, functional periods, charging, and maintenance times.

Preliminary investigations of nonlinear modeling of aircraft synchronous generators using neural networks are presented. Aircraft synchronous generators with high power density tend operate at current-levels proportional to the magnetic saturation region of the machine's material. The nonlinear model accounts for magnetic saturation of the generator, which causes the winding flux linkages and inductances to vary as a function of current. Finite element method software is used to perform a parametric sweep of direct, quadrature, and field currents to extract the respective flux linkages. This data is used to train a neural network which yields current as a function of flux linkage. The neural network is implemented in a Simulink synchronous generator model and simulation results are compared with a previously developed linear model. Results show that the nonlinear neural network model can more accurately describe the responsiveness and performance of the synchronous generator.

Social stressors in long-duration spaceflight (LDSF) have serious implications for crew effectiveness and mission safety. This paper reviews potential stressors and presents habitat and organizational design considerations to reduce perceived demand from social stressors in four areas: privacy and personal space, isolation, interpersonal interactions, and cultural differences. Results can serve as guidelines for the design of future LDSF missions and spacecraft, and will benefit attempts to develop an accurate model of stress in the spaceflight domain.

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.

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.

With the development and licensing of inland, state-owned spaceports, and the ongoing development of several new reusable launch vehicles (RLV), the space launch industry is undergoing a significant transformation. As a result, there is a need to reevaluate current launch risk analysis methodologies and practices, which so far have revolved around the conservative casualty expectation analysis developed in the 1950s. Furthermore, an important aspect of launch risk analysis which gives rise to its complexity is its multidisciplinary nature. In analyzing such risk, the physics of and interactions between the varieties of hazards produced by launch vehicles breakups must be captured, modeled and, their effects analyzed. In this paper we discuss how a well-designed multidisciplinary modeling and analysis platform could be a significant step toward reducing the complexity just mentioned.

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.

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].

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.

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.