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The term “productivity” all too often has becomes a buzz-word, ultimately diminishing its perceived importance. However, productivity is the major concern of any team, and therefore must be defined to gain an appropriate understanding of how a system is actually working. Here, productivity means the level of contribution to the throughput of a system such as defined in the Theory of Constraints. In the field of space exploration, the throughput is the number of milestones of the mission accomplished as well as the potential survival during extreme events (due to failures or other unplanned events). For a time tasks were accomplished by expert individuals (e.g., an astronaut), but recently team structures have become the norm. It is clear that with increased mission complexity, “no single entity can have complete knowledge of or the abilities to handle all matters” [10].

The aim of this work is to apply an innovative adaptive ℒ1 techniques to control flutter phenomena affecting highly flexible wings and to evaluate the efficiency of this control algorithm and architecture by performing the following tasks: i) adaptation and analysis of an existing simplified nonlinear plunging/pitching 2D aeroelastic model accounting for structural nonlinearities and a quasi-steady aerodynamics capable of describing flutter and post-flutter limit cycle oscillations, ii) implement the ℒ1 adaptive control on the developed aeroelastic system to perform initial control testing and evaluate the sensitivity to system parameters, and iii) perform model validation and calibration by comparing the performance of the proposed control strategy with an adaptive back-stepping algorithm. The effectiveness and robustness of the ℒ1 adaptive control in flutter and post-flutter suppression is demonstrated.

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.

Co-Optimization of Fuels and Engines initiative (Co-Optima) of the U.S Department of Energy started investigations on several candidates of biofuels and blends for internal combustion engines. At this stage, only a few biomass-derived fuel blendstocks (including ethanol) for advanced spark-ignition engines have been selected using enhanced screening criteria, which included boiling point, toxicity, research octane number, octane sensitivity, and economical distribution system, etc. Ethanol, of which this paper is focused on, is also an important fuel because of its high-octane number which in turn promotes advance ignition timing and higher thermal efficiencies in reciprocating engines. Measurements of laminar burning velocity (LBV) is a key metric to understand fuel performance and applicability in engines. Furthermore, in order to quantify more complicated, and practical, burning regimes such as turbulent combustion much of the underlying theory requires knowledge of LBV.

The biofuel and engine co-development framework was initiated at Sandia National Labs. Here, the synthetic biologists develop and engineer a new platform for drop-in fuel production from lignocellulosic biomass, using several endophytic fungi. Hence this process has the potential advantage that expensive pretreatment and fuel refining stages can be optimized thereby allowing scalability and cost reduction; two major considerations for widespread biofuel utilization. Large concentrations of ketones along with other volatile organic compounds were produced by fungi grown over switchgrass media. The combustion and emission properties of these new large ketones are poorly known.

The 2,4-dimethyl-3-pentanone (DIPK) is a promising biofuel candidate for automotive applications that is produced by the endophytic fungal conversion process which can be optimized for widespread utilization. There are some studies in the literature on combustion properties of DIPK, such as ignition delay times and laminar burning velocity (LBV) measurements. However, most studies are conducted one atmospheric (atm) pressure which are far away from the high-pressure conditions present inside reciprocating engines. Therefore, we present LBV measurements at high pressures up to 10 atm for this fuel using a spherical flame speed facility. It is known that the flame in a constant volume chamber develops cellular structure (hydrodynamic instability) as the initial pressure increases because of the reduction in flame thickness. In addition, the diffusional-thermal instability prevents experiments for rich mixtures because of the reduction of Lewis number (Le).

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.

A gasoline engine with an electronically controlled fuel injection system has substantially better fuel economy and lower emissions than a carburetted engine. In general, the stability of engine operation is improved with fuel injector, but the stability of engine operation at idle is not improved compared with a carburetted gasoline engine. In addition, the increase in time that an engine is at idle due to traffic congestion has an effect on the engine stability and vehicle reliability. Therefore, in this research, we will study the influence of fuel injection timing, spark timing, dwell angle, and air-fuel ratio on engine stability at idle.

This paper reviews the literature which identifies the causes, consequences and cures for engine knock as it affects high performance engines. The physical events of normal and abnormal combustion are described. The observed variations in combustion phenomenon are explained through chemical kinetics. A mathematical model of combustion which can predict knock in an engine cylinder is summarized. Several mechanisms of knock induced damage are outlined. Design and operating considerations which affect an engine's propensity to knock are discussed. Terms that have become associated with combustion in general and the knocking phenomenon in particular are collected and examined

The application of Statistical Process Control and Design of Experiment methods in the research laboratory can lead to significant gains in the Powertrain development process. Empirical methods such as Design of Experiments, Regression, and Neural Network techniques can be applied to help researchers gain better understanding of the cause and effect relationships of emission, alternative fuel source, performance, fuel economy, and engine management system - calibration studies. The use of these empirical modeling techniques along with model based Genetic Algorithm, Gradient, or Constraint based solution search methods will help identify the “process settings” that improve fuel economy, improve performance, and reduce pollutants. Since empirical methods are fundamentally based on the acquired test data, it is vitally important that the laboratory measurements are repeatable, consistent, and void of sources of variance that have a significant effect on the acquired test data.

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.

Engine dynamometer testing of homogeneous charge, spark ignition lean burn engines fueled by natural gas, hydrogen/natural gas blends and neat hydrogen was conducted to determine if NOx emissions from blended fuel operation can be reduced below those generated from natural gas operation, approaching those due to a 100% hydrogen fueled engine. The preliminary tests were conducted at the University of Central Florida/Florida Solar Energy Center on an eight cylinder automotive engine. The results indicate that the hydrogen/natural gas fuel has the potential of meeting highly restrictive NOx levels. Sandia National Laboratories conducted follow-on, comparative tests using a single cylinder research engine. The Sandia results indicate that the proposed CARB EZEV standard for NOx can be met without exhaust gas aftertreatment using a 30% hydrogen (by volume) / 70% natural gas blend fuel in a constant speed/power, hybrid vehicle application which achieves 60 MPG gasoline equivalent efficiency.

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.

In this paper, we introduce the use of ontologies to implement the information developed and organized by resource planning tools into standard project management documents covering integrated cost, resource modeling and analysis, and visualization. The basic upper ontology used for NASA Space Operations is explained and the results obtained are discussed. This ontology-centered approach is looking for tighter connections between software, hardware, and systems engineering.

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.

In this study we consider the coordinated exploration of an unfamiliar Martian landscape by a swarm of small autonomous rovers, called Swarmies, simulated in a distributed setting. With a sustainable program of return missions to and from Mars in mind, the goal of said exploration is to efficiently prospect the terrain for water meant to be gathered and then utilized in the production of rocket fuel. The rovers are tasked with relaying relevant data to a home base that is responsible for maintaining a mining schedule for an arbitrarily large group of rovers extracting water-rich regolith. For this reason, it is crucial that the participants maintain a wireless connection with one another and with the base throughout the entire process. We describe the architecture of our simulation which is composed of HLA-compliant components that are visualized via the Distributed Observer Network tool developed by NASA.

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.

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.

Laminar burning velocity (LBV) measurements are reported for promising high-performance fuels selected as drop-in transportation fuels to automotive grade gasoline as part of the United States Department of Energy’s Co-Optimization of Fuels and Engines Initiative (Co-Optima). LBV measurements were conducted for ethanol, methyl acetate, and 2-methylfuran with synthetic air (79.0 % N2 and 21.0 % O2 by volume) within a constant-volume spherical combustion rig. Mixture initial temperature was fixed at 428±4 K, with the corresponding initial pressure of 1.00±0.02 atm. Current LBV of ethanol is in good agreement with literature data. LBV of ethanol and 2-methylfuran showed similar values over the range of equivalence ratios, while methyl acetate exhibited an LBV significantly lower over the range of tested equivalence ratios. The maximum laminar burning velocity occurred at slightly richer equivalence ratio from the stoichiometric value for all fuels tested.