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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.

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].

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.

Efforts to develop sensor and control system technology to monitor air quality for life support have resulted in the development and preliminary testing of a concept based on expert systems and ion trap mass spectrometry (ITMS). An ITMS instrument provides the capability to identify and quantitate a large number of suspected contaminants at trace levels through the use of a variety of multidimensional experiments. An expert system provides specialized knowledge for control, analysis, and decision making. The system is intended for real-time, on-line, autonomous monitoring of air quality. The key characteristics of the system, performance data and analytical capabilities of the ITMS instrument, the design and operation of the expert system, and results from preliminary testing of the system for trace contaminant monitoring are described.

The PESTO (Photosynthetic Experiment System Testing and Operation) experiment flew in the Biomass Production System (BPS) to International Space Station (ISS) on STS-110 (Atlantis) April 8, 2002, and returned on STS-111 (Endeavour) June 19, 2002, after 73 days in space. The ground control was conducted on a two-week delay at Kennedy Space Center in a BPS unit under environmental conditions comparable to ISS. Wheat (Triticum aestivum cv Apogee) and Brassica rapa cv Astroplant were independently grown in root modules for multiple grow-outs. On-orbit harvests, root modules exchanges and primings, seeds imbibitions, and gas and water samplings occurred at periodic intervals; all were replicated in ground controls. Many operations required crew handling and open access to individual chambers, allowing the exchange of microorganisms between the crew environment and the BPS modules.

Understanding the effects of dynamic thermal and vacuum regeneration on VOC desorption kinetics is needed for the development of regenerable trace contaminant control air revitalization systems. The effects of temperature and vacuum quality on the desorption kinetics of ethanol from Carbosieve SIII were examined using 1 hour regeneration cycles. The effect of vacuum quality on ethanol desorption was studied by exposing adsorption tubes loaded with ethanol to low pressures (1.0, 0.5, 0.3, and 0.12 atm) at various thermal regeneration temperatures (160, 100, 70, and 25 °C). At 1 atm of pressure, ethanol removal was found to increase from 2% at 25 °C, to 25% at 70 °C, to 55% at 100 °C, and to 77% at 160 °C. Decreasing the atmospheric pressure from 1 to 0.1 atm for 1 hr did not significantly enhance Carbosieve SIII regeneration at ambient temperatures (25 °C). However, heating the adsorbent at low pressures enhanced its regeneration.

This report describes the design, assembly, and testing of a modified, re-circulating drip flow reactor to quantify the electrical, optical, and thermal performance of solid-state ultraviolet (UV) lighting and semi-conducting photocatalyst for potable water disinfection by advanced oxidation processes. The reactor test assembly incorporates high-output UV-A Light Emitting Diodes (LEDs) with active thermal control to reject heat and generate reactive oxygen species from immobilized titanium dioxide attached to borosilicate glass in the laminar flow stream. Compared with UV-excimer and UV-mercury arc lamps, the UV-A LED system demonstrated excellent thermal stability and good electrical and optical performance.

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.

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.

Operations involving autonomous vehicles require knowledge of the surrounding environment including other moving vehicles. The use of vision has been regarded as an enabling technology that can provide such information. Several important applications that would benefit from this technology is autonomous aerial refueling (AAR) and target tracking. This paper considers a sensor fusion approach using traditional IMU/GPS sensors with vision to facilitate the state estimation problem of moving targets. The proposed method makes use of a moving monocular camera to estimate the relative position and orientation of targets within the image by exploiting a known reference motion. The vision state estimation problem is solved using an homography approach that employs images containing both the reference and target vehicles. A simulation involving an unmanned aerial vehicle (UAV) and two ground vehicles is documented in this paper to demonstrate the algorithm and its accuracy.

The removal of volatile organic compounds (VOCs) from the air aboard spacecrafts is necessary to maintain the health of crewmembers. The use of photocatalysis has proven effective for the removal of VOCs. A majority of studies have focused on thin films, which have a low adsorption capacity for contaminants and intermediate oxidation byproducts. Thus, this study investigates the use of adsorbent materials impregnated or coated with titania to: (1) provide a system that can remove VOCs for a period of time in the absence of UV irradiation to reduce power requirements and/or offer contaminant removal in the event of lamp failure and (2) improve the photocatalytic oxidation efficiency by concentrating VOCs and intermediate oxidation byproducts near the surface of the photocatalyst. Two adsorbent materials (porous silica gel and BioNuchar120 activated carbon) and glass beads were tested as catalyst supports for the destruction of a target VOC, in this case methanol (Co = 50 ppmv).

The battery is a central part of the vehicle’s electrical system and has to undergo cycling in a wide variety of conditions while providing an acceptable service life. Within a typical distribution chain, automotive lead-acid batteries can sit in storage for months before delivery to the consumer. During storage, batteries are subjected to a wide variety of temperature profiles depending on facility-specific characteristics. Additionally, batteries typically do not receive any type of maintenance charge before delivery. Effects of storage time, temperature, and maintenance charging are explored. Flooded lead-acid batteries were examined immediately after storage and after installation in vehicles subjected to normal drive patterns. While phase composition is a major consideration, additional differences in positive active material (PAM) were observed with respect to storage parameters.

The candidate crops that have been considered by NASA for providing moderate quantities of supplemental food for crew's consumption during near term or long duration missions include minimally processed “salad” species. Lettuce (cv. Flandria), radish (cv. Cherry Bomb II) and green onion (cv. Kinka) plants were grown under cool-white fluorescent (CWF) lamps with light intensities of 8.6, 17.2, or 25.8 mol m−2 d−1, at air temperatures of 25 and 28 °C, 50% relative humidity, and 1200 µmol mol−1 CO2. Following 35 days growth, final edible mass yields were recorded. All three species grown at 25 °C showed an increase in edible fresh mass and growth rates as light intensity increased. When grown at 28 °C however, the edible fresh mass and crop growth rate of radish, lettuce and onion was significantly reduced at all light intensities when compared to yields at 25 °C. Overall, results indicated that all three crops were sensitive to changes in light intensity and temperature.

Carbosieve SIII was used to filter dichloromethane (DCM) from a simulated spacecraft gas stream. This adsorbent was tested as a possible commercial-off-the-shelf (COTS) filtration solution to controlling spacecraft air quality. DCM is a halocarbon commonly used in manufacturing for cleaning and degreasing and is a typical component of equipment offgassing in spacecraft. The performance of the filter was measured in dry and humid atmospheres. A known concentration of DCM was passed through the adsorbent at a known flow rate. The adsorbent removed dichloromethane until it reached the breakthrough volume. Carbosieve SIII exposed to dry atmospheric conditions adsorbed more DCM than when exposed to humid air. Carbosieve SIII is a useful thermally regenerated adsorbent for filtering DCM from spacecraft cabin air. However, in humid environments the gas passes through the filter sooner due to co-adsorption of additional water vapor from the atmosphere.

A power electronics module was equipped with an evaporative spray cooling nozzle assembly that served to remove waste heat from the silicon devices. The spray cooling nozzle assembly took the place of the standard heat sink, which uses single phase convection. The purpose of this work was to test the ability of spray cooling to enable higher power density in power electronics with high temperature coolant, and to be an effective and lightweight system level solution to the thermal management needs of aerospace vehicles. The spray cooling work done here was with 95 °C water, and this data is compared to 100 °C water/ propylene glycol spray cooling data from a previous paper so as to compare the spray cooling performance of a single component liquid to that of a binary liquid such as WPG. The module used during this work was a COTS module manufactured by Semikron, Inc., with a maximum DC power input of 180 kW (450 VDC and 400 A).

The development of a spaceflight-rated Porous Tube Insert Module (PTIM) nutrient delivery tray has facilitated a series of studies evaluating various aspects of water and nutrient delivery to plants as they would be cultivated in space. We report here on our first experiment using the PTIM with a software-driven feedback moisture sensor control strategy for maintaining root zone wetness level set-points. One-day-old wheat seedlings (Tritium aestivum cv Apogee; N=15) were inserted into each of three Substrate Compartments (SCs) pre-packed with 0.25–1 mm Profile™ substrate and maintained at root zone relative water content levels of 70, 80 and 90%. The SCs contained a bottom-situated porous tube around which a capillary mat was wrapped. Three Porous Tubes were planted using similar protocols (but without the substrate) and also maintained at these three moisture level set-points. Half-strength modified Hoagland’s nutrient solution was used to supply water and nutrients.