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Dimensional Management (DM) is a methodology to predict and control the impact of variation on assembly from, fit, and function. Application of Dimensional Management tools and other modeling and simulation techniques are combined in a process called 3D Re-Engineering for application to existing production designs. Analytical techniques for predicting the impact of variation on assembly fit, and corresponding methods for controlling variation are presented, as used in a production environment for root cause corrective action on existing assembly fit problems. Assembly variation analysis is typically performed early in the product development phases, by coordinating datums, assembly sequences, assembly methods, and detail part tolerances across the product development team.

Modern aircraft are aerodynamically designed at the edge of flight stability and therefore require high-response-rate flight control surfaces to maintain flight safety. In addition, to minimize weight and eliminate aircraft thermal cooling requirements, the actuator systems have increased power-density and utilize high-temperature components. This coupled with the wide operating temperature regimes experienced over a mission profile may result in detrimental performance of the actuator systems. Understanding the performance capabilities and power draw requirements as a function of temperature is essential in properly sizing and optimizing an aircraft platform. Under the Air Force Research Laboratory's (AFRL's) Integrated Vehicle and Energy Technology (INVENT) Program, detailed models of high performance electromechanical actuators (HPEAS) were developed and include temperature dependent effects in the electrical and mechanical actuator components.

An automated system drills the outer moldline holes on a military aircraft wing. Currently, the operator manually checks countersink diameter every ten holes as a process quality check. The manual method of countersink inspection (using a countersink gauge with a dial readout) is prone to errors both in measurement and transcription, and is time consuming since the operator must stop the automated equipment before measuring the hole. Machine vision provides a fast, non-contact method for measuring countersink diameter, however, data from machine vision systems is frequently corrupted by non-gaussian noise which causes traditional model fitting methods, such as least squares, to fail miserably. We present a solution for circle measurement using a statistically robust fitting technique that does an exceptional job of identifying the countersink even in the presence of large amounts of structured and non-structured noise such as tear-out, scratches, surface defects, salt-and-pepper, etc.

A study was conducted to investigate the impacts of obstacles on pilot performance, workload, and perceptions of safety in a visual flight rule (VFR) obstacle-rich environment (ORE). The study was conducted using a piloted simulation of a single-rotor, multi-engine helicopter operating in a highly detailed urban visual scene database. The database contained multiple obstacle types, with variable obstacle heights and densities. Nine pilots completed the approaches and departures into and out of a heliport located in the center of the generic urban environment. Two flight routes offered unique presentations of terrain and obstacle types. Obstacle height/density and time of day/lighting parameters were systematically manipulated. A multi-dimensional data collection methodology employing the simultaneous collection of direct aircraft state, pilot performance data, pilot physiological data and pilot subjective responses was employed.

Advanced Data Format (ADF) is a portable hierarchical database software library developed by The Boeing Company under contract with NASA [1] and with assistance from industry partners. ADF was designed and built to directly support the CFD General Notation System (CGNS1) project. The CGNS project defines conventions and supplies software to facilitate the exchange of computational fluid dynamics (CFD) data between sites and between applications, and it allows stable archiving of CFD data. CGNS is implemented on the ADF foundation and is focused on the needs of the CFD community. This paper details the design, implementation, use, and future direction of ADF.

Crew health is dependent on the concentration of carbon dioxide in the atmosphere breathed. Often, models used for concentration have used the assumption that each module of the space station is well mixed, i.e. that the CO2 concentration is constant throughout the module. In this paper, Computational Fluid Dynamics (CFD) modeling is used to assess and validate the accuracy of that assumption. The concentration of carbon dioxide as calculated by CFD was compared to the concentration as calculated by a lumped parameter model. The assumption that the module is well mixed allows the use of relatively simple models, which can be developed and run quickly in order to support decisions for on-orbit analysis. CFD models generate more detailed information, such as CO2 gradients within the modules and airflow and mixing characteristics. However, CFD models, particularly transient models, take longer to develop and use.

An air quality simulation and assessment (AQSA) model was developed to simulate/evaluate the integrated system performance and obtain air quality characteristics and air contaminants inside the habitable compartments. This model applies both fixed control volume and quasi-steady-state approach for a multi-volume system to assess system performance, operating constraints, and capabilities. The model also integrates a state-of-the-art probabilistic analysis tool, UNIPASS, to compute failure probability due to the uncertainties of variables. In addition, this integrated model also predicts the most likely outcomes for analyzing risks and uncertainties as well as for quantitative toxicological evaluation. This model has been successfully and independently corrected/verified by NASA/JSC to be a very effective, reliable, and accurate tool, while providing savings in both the cost and time of the analysis.

Defining a process for integrating human modeling within the design and verification activities of the International Space Station (ISS) has proven to be as important as the simulations themselves. The process developed (1) ensured configuration management of the required digital mockups, (2) provided consistent methodology for simulating and analyzing human tasks and hardware layout, (3) facilitated an efficient method of communicating design requirements and relaying satisfaction of contract requirements, and (4) provided substantial cost savings by reducing the amount of late redesign and expensive mockup tests. Human simulation is frequently the last step in the design process. Consequently, the influence it has on product design is minimal and oftentimes being used as a post-design verification tool.

This paper presents results of the CFD study aimed at evaluation of the CO2 concentration within the Shuttle Orbiter Middeck during the Launch on Need (LON) Crew Rescue flight. An assessment of the Middeck ventilation characteristics has been performed for two possible ventilation arrangements. A recommendation to use the ventilation system configuration with the open aft floor diffuser has been made on the basis of a three-dimensional airflow and CO2 gradient analysis.

The paper presents the results of a CFD study for predictions of ventilation characteristics and convective heat transfer within the Shuttle Orbiter middeck cabin in the presence of seven suited crewmember simulation and Individual Cooling Units (ICU). For two ICU arrangements considered, the thermal environmental conditions directly affecting the ICU performance have been defined for landing operation. These data would allow for validation of the ICU arrangement optimization.

The trend of moving towards model-based design and analysis of new and upgraded aircraft platforms requires integrated component and subsystem models. To support integrated system trades and design studies, these models must satisfy modeling and performance guidelines regarding interfaces, implementation, verification, and validation. As part of the Air Force Research Laboratory's (AFRL) Integrated Vehicle and Energy Technology (INVENT) Program, standardized modeling and performance guidelines have been established and documented in the Modeling Requirement and Implementation Plan (MRIP). Although these guidelines address interfaces and suggested implementation approaches, system integration challenges remain with respect to computational stability and predicted performance over the entire operating region for a given component. This paper discusses standardized model evaluation tools aimed to address these challenges at a component/subsystem level prior to system integration.

A highly modified F/A-18 aircraft is being used to demonstrate that aeroelastic wing twist can be used to roll a high performance aircraft. A production F/A-18A/B/C/D aircraft uses a combination of aileron deflection, differential horizontal tail deflection and differential leading edge flap deflection to roll the aircraft at various Mach numbers and altitudes. The Active Aeroelastic Wing program is demonstrating that aeroelastic wing twist can be used in lieu of the horizontal tail to provide autonomous roll control at high dynamic pressures. Aerodynamic and loads data have been gathered from the Phase I AAW flight test program. Now control laws have been developed to exploit aeroelastic wing twist and provide autonomous flight control of the AAW aircraft during Phase II. Wing control surfaces are being deflected in non-standard ways to create aeroelastic wing twist and develop the required rolling moments without use of the horizontal tail.

This paper examines the capability of the Reynolds-averaged thin-layer Navier-Stokes codes to simulate the results from a two-dimensional aileron effectiveness test. This unique test was carried out in the IAR high Reynolds number wind tunnel and addressed the effects of Reynolds number, Mach number and angle-of-attack on aileron effectiveness. The test results showed a highly nonlinear variation of lift for downward trailing edge deflections. It provides a valuable database for using CFD to determine the adequacy of the corrections applied to the experimental data due to the presence of the wind tunnel walls, and for assessing the current CFD capability to model the flowfield with separation. CFD predictions are obtained by using CFL3D with the Spalart-Allmaras turbulence model and TLNS2D with the modified Johnson-King turbulence model.

The U. S. Laboratory (USL) module was added to the International Space Station (ISS) in Flight 5A, which would boost the Environmental Control & Life Support System (ECLSS) functional capabilities of the ISS. In the USL cabin aisle way, the air circulation is provided by a Temperature & Humidity Control (THC) system. To provide adequate ventilation under various open/close combinations of the rack panels, it would be very challenging by conducting many tests prior to the launch of Flight 5A. Computational fluid dynamics (CFD) simulation technology is utilized to investigate the airflow in the U.S. Lab for various operating scenarios. A CFD model, which includes the supply diffusers, the return registers, the ventilation of the temporary crew quarter, the gap between the outer pressure shell and all the racks, is modeled. The ventilation performance for the cabin aisle way and air behind panels is addressed.

The objective of this study is to evaluate ventilation efficiency regarding to the International Space Station (ISS) cabin ventilation during the ISS assembly mission 1J. The focus is on carbon dioxide spatial/temporal variations within the Node 2 and attached modules. An integrated model for CO2 transport analysis that combines 3D CFD modeling with the lumped parameter approach has been implemented. CO2 scrubbing from the air by means of two ISS removal systems is taken into account. It has been established that the ventilation scheme with an ISS Node 2 bypass duct reduces short-circuiting effects and provides less CO2 gradients when the Space Shuttle Orbiter is docked to the ISS. This configuration results in reduced CO2 level within the ISS cabin.

The desire to operate rotorcraft in icing conditions has renewed the interest in developing high-fidelity analysis methods to predict ice accumulation and the ensuing rotor performance degradation. A subset of providing solutions for rotorcraft icing problems is predicting two-dimensional ice accumulation on rotor airfoils. While much has been done to predict ice for fixed-wing airfoil sections, the rotorcraft problem has two additional challenges: first, rotor airfoils tend to experience flows in higher Mach number regimes, often creating glaze ice which is harder to predict; second, rotor airfoils oscillate in pitch to produce balance across the rotor disk. A methodology and validation test cases are presented to solve the rotor airfoil problem as an important step to solving the larger rotorcraft icing problem. The process couples Navier-Stokes CFD analysis with the ice accretion analysis code, LEWICE3D.

After launch and activation activities, the Columbus module started its operational life on February 2008 providing resources to the internal and external experiments. In March 2008 two US Payloads were successfully installed into Columbus Module: Microgravity Sciences Glovebox (MSG) and a US payload of the Express rack family, Express Rack 3, carrying the European Modular Cultivation System (EMCS) experiment. They were delivered to the European laboratory from the US laboratory and followed few months later by similar racks; Human Research Facility 1 (HRF1) and HRF2. The following paper provides an overview of US Payloads, giving their main features and experiments run inside Columbus on year 2008. Flight issues, mainly on the hydraulic side are also discussed. Engineering evaluations released to the flight control team, telemetry data, and relevant mathematical models predictions are described providing a background material for the adopted work-around solutions.

Proper design of the air ventilation system is critical to maintaining a healthy environment for the ISS crew. In this study, a computational fluid dynamic model was used to model the air circulation in Node 1 to identify the locations where there are low air velocities under nominal operating conditions and several reduced ventilation flow conditions. The reduced ventilation flow conditions analyzed were loss of cabin air fan, loss of inter-module ventilation from Node 1 to the US Lab, and loss of inter-module ventilation from the airlock to Node 1. For nominal operation of the ventilation system, about 5% of the node had air velocity of between 1 and 5 ft/min and 14% of the node had air velocity of between 5 and 10 ft/min. Loss of the cabin air fan and loss of Lab inter-module ventilation did not have a significant impact on the percentage of the node that would have low air circulation.

Computational Fluid Dynamics airflow models for the Waste and Hygiene Compartment (WHC) in the U.S. Laboratory module and Node 3 were developed and examined. The International Space Station (ISS) currently provides human waste collection and hygiene facilities in the Russian Segment Service Module (SM) which supports a three person crew. An additional set of Russian hardware, known as the system, is planned for the United States Operational Segment (USOS) to support expansion of the crew to six persons. Integration of the Russian system into the USOS incorporates direct Environmental Control and Life Support System (ECLSS) interfaces to allow more autonomous operation. A preliminary design concept was used to create a geometry model to evaluate the air interaction with the module cabin at varied locations and performance of the avionics fan placed in WHC. The Russian and the privacy protection bump-outs (Kabin) were included into the present modeling.

Ventilation characteristics of the Columbus module are numerically predicted on the basis of the Reynolds-Averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES) approaches. Effects of air supply diffuser modeling on computed flow are analyzed. An “effective diffuser” model that considerably reduces the number of computational cells for Columbus CFD ventilation analysis is proposed and tested. The computational models are verified by a comparison with the experimental data available. Special attention is paid to distinctions in fields of the time-averaged absolute velocity magnitude and the whole mean velocity that are due to the contribution of large-scale fluctuations. A technique to evaluate spatial distribution of the time-averaged absolute velocity magnitude using data of RANS steady-state predictions is suggested.