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The process of developing, parameterizing, validating, and maintaining models occurs within a wide variety of tools, and requires significant time and resources. To maximize model utilization, models are often shared between various toolsets and experts. Model integration is typically divided into two categories: model exchange and model co-simulation. Of these two categories, model co-simulation is typically regarded as the more complex and difficult to implement. Co-Simulation provides the ability to integrate models between different toolsets or incompatible versions of the same software. Additionally, it provides the capabilities for real-time simulations and hardware-in-the-loop test scenarios. This paper reviews some of the common co-simulation data communication methods including pipes and file input/output. The differences between serial and parallel, aka synchronous and asynchronous, communication patterns are also discussed.

The process of developing, parameterizing, validating, and maintaining models occurs within a wide variety of tools, and requires significant time and resources. To maximize model utilization, models are often shared between various toolsets and experts. One common example is sharing aircraft engine models with airframers. The functionality of a given model may be utilized and shared with a secondary model, or multiple models may run collaboratively through co-simulation. There are many technical challenges associated with model sharing and co-simulation. For example, data communication between models and tools must be accurate and reliable, and the model usage must be well-documented and perspicuous for a user. This requires clear communication and understanding between computer scientists and engineers. Most often, models are developed by engineers, whereas the tools used to share the models are developed by computer scientists.

The general benefits of automation are well documented. Order of magnitude improvements are achievable in processing speeds, production rates, and efficiency. Other benefits include improved process consistency (inversely, reduced process variation), reduced waste and energy consumption, and risk reduction to operators. These benefits are especially true for the automation of the aerospace paint removal (or "depaint") processes. Southwest Research Institute® (SwRI®) developed and implemented two systems in the early 1990s for depainting full-body fighter aircraft at Robins Air Force Base (AFB) at Warner Robins, Georgia, and Hill AFB at Ogden, Utah. These systems have been in production use, almost continuously for approximately 20 years, for the depainting of the F-15 Eagle and the F-16 Falcon fighter aircraft, respectively.

Cabin air quality is of continuing importance [1]. Contamination of air with particulates or vapors has the potential of affecting the health of passengers and flight crew. Therefore, measures are required to maintain acceptable levels of cabin air quality. One potential source of cabin air contamination is lubricating oils used in the engines. Type II oils are required for the main engines, but Type I or Type II oils can be used for the APU, with Type I recommended by some engine manufacturers for its cold-start properties. Southwest Research Institutes (SwRI®) Department of Emissions Research used an internally developed analytical method called Direct Filter Injection/Gas Chromatograph (DFI/GC™) to analyze for volatile fractions of lubricating oil contaminants on Environmental Control System (ECS) components. Samples of two standard Type II aviation turbine lubricating oils were analyzed with the DFI/GC™ method and their spectra examined.

Atmospheric corrosion of steels, aluminum alloys, and Al-clad aluminum alloys is a problem for many civil engineering structures, commercial and military vehicles, and aircraft. Paint is usually the primary means to prevent the corrosion of steel bridge components, automobiles, trucks, and aircraft. Under ideal conditions, the coating provides a continuous layer that is impervious to moisture. At present, maintenance cycles for commercial and military aircraft and ground vehicles, as well as engineered structures, is based on experience and appearance rather than a quantitative determination of coating integrity. To improve the maintenance process and reduce costs, sensors are often used to monitor corrosion. The present suite of sensors designed to detect corrosion and marketed to predict the lifetime of the engineered components, however, are not useful for determining the condition of the protective paint coatings.

Excessive interior noise and vibration in propeller driven general aviation aircraft can result in poor pilot communications with ground control personnel and passengers, and, during extended flights, can lead to pilot and passenger fatigue. Noise source/path identification technology applicable to single engine propeller driven aircraft were employed to identify interior noise sources originating from structure-borne engine/propeller vibration, airborne propeller transmission, airborne engine exhaust noise, and engine case radiation. The approach taken was first to conduct a Principal Value Analysis (PVA) of an in-flight noise and vibration database acquired on a single engine aircraft to obtain a correlated data set as viewed by a fixed set of cabin microphones.

Control of structure borne noise transmission into an aircraft cabin generated from component excitation, such as rotor/engine vibration imbalance or firing excitations or from auxiliary equipment induced vibrations, can be studied empirically via impedance characterization of the system components and application of appropriate component coupling procedures. The present study was aimed at demonstrating the usefulness of such impedance modeling techniques as applied to a Bell 206B rotorcraft and a Cessna TR182 general aviation aircraft. Simulated rotor/engine excitations were applied to the assembled aircraft systems to provide baseline structure borne noise transmission data. Thereafter, impedance tests of the system components were carried out to provide a data base from which system component coupling studies were carried out.

The growing usage of Unmanned Aerial Vehicles (UAVs) for aerial surveillance and reconnaissance in military applications calls for lightweight, reliable powerplants that burn heavy distillate fuels. While mass-produced engines exist that provide adequate power-to-weight ratio in the low power class needed for UAVs, they all use a spark-ignited combustion system that requires high octane fuels. Southwest Research Institute (SwRI) has embarked upon an internal research effort to design and demonstrate an engine that will meet the requirements of high power density, power output compatible with small unmanned aircraft, heavy-fuel combustion, reliable, durable construction, and producible design. This effort has culminated in the successful construction and operation of a demonstrator engine.

RADIATION can produce almost instantaneous failure of modern aircraft lubricants, tests at Southwest Research Institute show. Two types of failures demonstrated are rapid viscosity rise and loss of heat conductivity. Furthermore, it was found that lubricants can become excessively corrosive under high-level radiation. Generally speaking, the better lubricants appeared to improve in performance while marginal ones deteriorated to a greater extent under radiation. When the better lubricants were subjected to static irradiation prior to the deposition test, there was a minor increase in deposition number as the total dose was increased.