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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.

The requirement of “zero defects” is rapidly finding its way as a “standard” of quality in numerous quarters. This phrase has great psychological appeal, and is often taken literally at all levels in an organization even though quality motivation may be the intention. It is common to believe that when zero defects are found in the sample, this must be the case for “all the rest” as well. In this paper the technical side of “zero defects” is examined. We look at the statistics of zero defects and show what is implied about lot or process quality when zero defects is the actual sample outcome. The focus is on attribute measurements and includes some special cases where a significant measurement error exists and cases where a Bayesian statistical analysis may be appropriate.

An integrated simulation tool has been developed, which is applicable to a wide range of design issues. A key feature introduced for the first time by this new tool is that it is truly a single code, with identical handling of engine, powertrain, vehicle, hydraulics, electrical, thermal and control elements. Further, it contains multiple levels of engine models, so that the user can select the appropriate level for the time scale of the problem (e.g. real-time operation). One possible example of such a combined simulation is the present study of engine block vibration in the mounts. The simulation involved a fully coupled model of performance, thermodynamics and combustion, with the dynamics of the cranktrain, engine block and the driveline. It demonstrated the effect of combustion irregularity on engine shaking in the mounts.

Oil pumpability in passenger car gasoline engines was well-characterized by an ASTM program and by individual researchers in the 1970's and early 1980's. Oil pumpability in diesel engines however, was not investigated to any significant extent until the mid-1980's. This study was initiated to define the performance of several commercial viscosity modifiers in different formulations containing 3 detergent-inhibitor (DI) additive packages and 4 basestock types. The test oils were run at -18°C (0°F) in a Cummins NTC-400 diesel engine. The results, when statistically analyzed, indicated that a new, second generation olefin copolymer (OCP) viscosity modifier had better performance than a first generation OCP and, furthermore, had performance equal to a polymethacrylate (PMA) viscosity modifier. The analysis also showed that one DI/base stock combination had a significant effect on performance.

In the modern and fast growing automotive sector, reliability & durability are two terms of utmost importance along with weight & cost optimization. Therefore it is important to explore new technology which has less weight, low manufacturing cost and better strength. The new technology developed always seek for a quick, cost effective and reliable methodology for its design validation so that any modification can be made by identifying the failures. This paper presents the rig level test methodology to validate and to correlate the CAE derived strain levels, life cycle & failure mode of newly developed light weight stabilizer link for EV Bus suspension

Understanding customer expectations is critical to satisfying customers. Holding customer clinics is one approach to set winning targets for the engineering functional measures to drive customer satisfaction. In these clinics, customers are asked to operate and interact with vehicle systems or subsystems such as doors, lift gates, shifters, and seat adjusters, and then rate their experience. From this customer evaluation data, engineers can create customer loss or preference functions. These functions let engineers set appropriate targets by balancing risks and benefits. Statistical methods such as cumulative customer loss function are regularly applied for such analyses. In this paper, a new approach based on the Taguchi method is proposed and developed. It is referred to as Taguchi Customer Loss Function (TCLF).

The onboard “SODART” telescope silicon detector cooling system of the “Spectrum-X-Gamma” observatory, which is designed for the space objects X-ray radiation study, is described. The scale-down model of the passive cooling system description and thermal vacuum test results of this model are given. In the real cooling system the minimal detector temperature at 300 mW heat release is expected about 107 K.

In automotive electronics on-board diagnostics does the fault diagnosis and reporting. It provides the level of robustness required for the control electronics against various faults. The amount of diagnostic information available via on board diagnostics are depends on the type of vehicle. Pre-supply fuel pump is the component in the common rail hydraulic system. It pumps the fuel from the fuel tank to the inlet valve of the high pressure fuel pump. Electronic control unit synchronizes its operation with high pressure fuel pump. A dedicated driver module in the ECU controls the operation of pre-supply fuel pump. The driver module consist of an ASIC with internal voltage, current monitoring modules for the fault diagnosis and the pre-drivers to control external HS and LS power stages. The software part of the OBD programmed in the internal memory of the ASIC. The “Rds_on” of the power MOSFETs are used for the fault detection purpose.

The simulation system “Roadrunner” has the ability to compute 3-dimensional vehicle behavior during simulated ABS-stops or Traction Control (TC) operation on a PC based test rig system. This can be done in real-time mode with fast DSP (digital signal processor) boards and an ABS/TC-ECU as a ‘Hardware-in-the-loop’ device (HIL) or off-line (non-real-time), on the PC only. In the off-line-mode, the PC additionally performs the ABS/TC control algorithms. The simulated system includes model equations for chassis and wheel movement, hydraulics and road to tire interactions. A driver model enables the reproduction of standard steering maneuvers.

This paper describes the initial works related to the study of Internal Combustion Engines, as an object of mechanical design, at the Universidad Tecnológica de Pereira. It is reported a concise, complete methodology for simple model of internal combustion engine. The emphasis of the paper is placed on the use of the in-cylinder parameters (pressure and temperature) and inertial loads in the crank-slider mechanism to derive the loads that act on all the components of the crank-slider mechanism as well as the theoretical output torque for a given geometrical structure and inertial properties. These loads can then be used to estimate the preliminary dimensions of engine components in the initial stage of engine development. To obtain the pressure and temperature inside the cylinder, under different operation parameters, such as air fuel ratio and spark angle advance, a Zero dimensional model is applied. The heat transfer from the cylinder and friction are not taken into account.

Presented in this paper is a brief review of momentum exchange theory for Jet Noise Suppression. “Experimental Results from Scale Model Tests” are included. These data exhibit peak to peak attenuation of 20 db along maximum exhaust noise azimuths at a nozzle pressure ratio of 3.1.

Vehicle dynamics is a discipline of mechanical engineering that benefited of significant improvements thanks to the progress of computational engineering. Vehicle dynamics engineers are using CAE for the development of a vehicle with MBS and FEA. The concurrent use of these two technologies is a standard in the automotive industry. However the current simulation process is not fully efficient because local geometrical and material nonlinearities are not accurately modeled in classical MBS software. This paper introduces a methodology for vehicle dynamics simulation integrating MBS capabilities in one single nonlinear FEA environment enabling an accurate modeling of nonlinearity in vehicles.

Mathematical modeling and control of artificial ecosystems, such as MELISSA, require first the study of physical and biological characteristics in optimal and limiting conditions. Following the previous determination of the stoichiometric equations (Spirulina compartment) and regarding the two phototrophic compartments of MELISSA (Rhodospirillaceae and Spirulina), we have first to focus our control study on the growth kinetics for the light source. In this paper, we recall the theoretical equations of microbial growth kinetics and emphasise the problem of the light transfer in a photobioreactor. We present their adaptations to our pilot plant taking into account technological and biological specifics (lamp spectrum, working illuminated volume, growth rate,…). We then develop the principles and structure of the control system and describe tests of both the hardware and software for several steady state configurations.

This paper describes the application of statistical techniques known as Design of Experiments (D.O.E.) to efficiently use the results of numerical analysis data in order to improve the configuration of automotive systems. The general framework of these techniques is presented in a format aiming at the design engineer as their end user. Besides, a case study is presented with the purpose of illustrating their practical use. The first step of the case study is to build predictive models for the behaviour of the automotive system being developed by means of the Response Surface Method (RSM), using the proper D.O.E. options. Once these predictive models are available, automatic numerical optimization algorithms are used to improve the responses of interest for given operating conditions. Finally, the automotive systems are robust designed taking into account that the operating conditions vary randomly.

The requirement for crew resource management (CRM), or aircrew coordination training (ACT) in military parlance, has been well documented and attested to. In addition, aircraft systems training has become more intense and more in-depth in the new aircraft designs, especially in multi-crew and complex aircraft such as the MV-22 Osprey Tiltrotor. (see Figure 1) Former training systems detailed training procedures that called for classroom training and simulation/simulator training followed by flight training. Improvements in aircraft flight skills training provide increased flying training capability coupled with reduced training time by integrating a mixed simulation/flight training syllabus, e.g. two to three simulation periods followed by one or two flight training periods covering the same material/skills. In addition, the simulation training will introduce new skills; the following flight periods will further refine/hone those skills.

The paper focuses and develops issues raised by the SAE paper ‘THE FUTURE OF VEHICLE ELECTRICAL POWER SYSTEMS AND THEIR IMPACT ON SYSTEM DESIGN’ [1] and describes the realisation of a vehicle with a 12 V architecture of flexible configuration and a power management function. The paper describes the methodology, reasoning and mission behind the creation of the vehicle, developed after collaborative exercises in Europe and the USA, and resulting in a joint programme involving a major vehicle manufacturer and a European system supplier. The electrical system is becoming the focus of activity world-wide due to rapid changes in vehicle requirements, in the areas of safety, environmental and functional demands. There are opportunities for:- (a) Improved starting (b) Integrated management of power generation and demand. (c) Higher system integrity (d) Higher efficiency (e) Improvement of the vehicle electrical environment, giving benefits in component cost.

Driver state monitoring is a crucial technology for enhancing road safety and preventing human error-caused accidents in the era of autonomous vehicles. This paper presents CogniSafe, a comprehensive driver monitoring system that uses deep learning and computer vision methods to detect various types of driver distractions and fatigue. CogniSafe consists of four modules: Driver anomaly detection and classification: A novel two-phase network that proposes and recognizes driver anomalies, such as texting, drinking, and adjusting radios, using multimodal and multiview input. Gaze estimation: A video-based neural network that jointly learns head pose and gaze dynamics, achieving robust and efficient gaze estimation across different head poses. Eye state analysis: A multi-tasking CNN that encodes features from both eye and mouth regions, predicting the percentage of eye closure (PERCLOS) and the frequency of mouth opening (FOM).

This paper is an extension of our previous work on the CHASE (Classification by Holistic Analysis of Scene Environment) algorithm, that automatically classifies the driving complexity of a road scene image during day-time conditions and assigns it an ‘Ease of Driving’ (EoD) score. At night, apart from traffic variations and road type conditions, illumination changes are a major predominant factor that affect the road visibility and the driving easiness. In order to resolve the problem of analyzing the driving complexity of roads at night, a brightness detection module is incorporated in our end-to-end nighttime EoD system, which computes the ‘brightness factor’ (bright or dark) for that given night-time road scene. The brightness factor along with a multi-level machine learning classifier is then used to classify the EoD score for a night-time road scene. Our end-to-end ‘Night-time EoD system’ is a real-time onboard system implemented and tested on road scene data collected in Japan.

“Digital Prototype” simulations have been used at DaimlerChrysler to achieve vehicle level NVH objectives. The effectiveness of these simulations to guide the design when faced with vehicle parameter uncertainties is discussed. These uncertainties include, but are not limited to, material properties, material gauges, damping, structural geometry, loads, boundary conditions and weld integrity. Manufacturing and assembly processes introduce variations in the nominal values of these parameters resulting in a scatter of vehicle level NVH simulation responses. An example of a high frequency NVH concern will be studied and modified to arrive at robust design guidance when faced with uncertainty. The validity of a “deterministic digital prototype” simulation model and its relevant role as a “trend predictor” rather than “absolute predictor” tool in guiding the design is also discussed.