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Hydrodynamic parameters play a major role in the dynamics and control of Autonomous Underwater Vehicles (AUV). The performance of an AUV is dependent on the parameter variations and a proper understanding of these parametric influences is essential for the design, modelling and control of high performance AUVs. In this paper, a six sigma framework for the sensitivity analysis of a flatfish type AUV is presented. Robust design techniques such as Taguchi’s design method and statistical analysis tools such as Pareto-ANOVA, and ANOVA are used to identify the hydrodynamic parameters influencing the dynamic performance of an AUV. In the initial study, it is found that when the vehicle commanded in forward direction, it is in bow down configuration which is unacceptable for AUV motion. This is because of the vehicle buoyancy and shape of the vehicle. So the sensitivity analysis of pitch angle variation is studied by using robust design techniques.

This paper attempts to assess the benefits of a unique distributed propulsion concept, known as the Multi-Gas Generator Fan (MGGF) system, over conventional turbofan engines on civilian vertical takeoff and landing (VTOL) applications. The MGGF-based system has shown the potential to address the fundamental technical challenge in designing a VTOL aircraft: the significant mismatch between the power requirements at lift-off/hover and cruise. Vehicle-level performance and sizing studies were implemented using the Grumman Design 698 tilt-nacelle V/STOL aircraft as a notional personal air vehicle (PAV), subjected to hypothetical single engine failure (SEF) emergency landing requirements and PAV mission requirements.

Reactivity controlled compression ignition (RCCI) is one of the most promising low temperature combustion (LTC) strategies to achieve higher thermal efficiencies along with ultra low oxides of nitrogen (NOx) and particulate matter emissions. Small single cylinder diesel engines of air-cooled type are finding increasing applications in the agriculture pump-set and small utility power generation owing to their lower cost and fuel economy advantages. In the present work, a small single cylinder diesel engine is initially operated under conventional combustion mode at rated speed, varying load conditions to establish the base line reference data. Then, the engine is modified to operate under RCCI combustion mode with a newly designed cylinder head to accommodate a high pressure, fully flexible electronically controlled direct diesel fuel injection system, a low pressure gasoline port fuel injection system and an intake air pre heater.

Advanced low temperature combustion (LTC) modes are most promising to reduce green house gas emissions owing to fuel economy benefits apart from simultaneously reducing oxides of nitrogen (NOx) and particulate matter (PM) emissions from diesel engines. Various LTC strategies have been proposed so far and each of these LTC strategies have their own advantages and limitations interms of precise ignition control, achievable load range and higher unburned emissions. In the present work, a small single cylinder diesel engine is initially operated under conventional combustion mode at rated speed, varying load conditions to establish the base line reference data. Then, the engine is modified to operate under different LTC strategies including Homogenous Charge Compression Ignition (HCCI), Premixed Charge Compression Ignition (PCCI) and Reactivity Controlled Compression Ignition (RCCI).

It is well established that reducing the compression ratio (CR) of a diesel engine leads to a significant increase in hydrocarbon (HC) and carbon monoxide (CO) emissions, especially in cold and transient conditions. Hence, it is essential to find new strategies to reduce the HC and CO emissions of a low compression ratio (LCR) diesel engine in transient conditions. In the present work, a detailed evaluation of different warm-up technologies was conducted for their effects on transient emissions characteristics of a single-cylinder naturally aspirated LCR diesel engine. For this purpose, the engine was coupled to an instrumented transient engine dynamometer setup. A transient cycle of 160 seconds with starting, idling, speed ramp-up and load ramp-up was defined, and the engine was run in automatic mode by the dynamometer. The experiments were conducted by overnight soaking the engine at a specified temperature of 25 deg.C.

In a direct-injection (DI) engine, charge motion and mixture preparation are among the most important factors deciding the performance and emissions. This work was focused on studying the effect of injector positioning on fuel-air mixture preparation and fuel impingement on in-cylinder surfaces during the homogeneous mode of operation in a naturally aspirated, small bore, 0.2 l, light-duty, air-cooled, four-stroke, spark-ignition engine modified to operate under the DI mode. A commercially available, six-hole, solenoid-operated injector was used. Two injector locations were identified based on the availability of the space on the cylinder head. One location yielded the spray-guided (SG) configuration, with one of the spray plumes targeted towards the spark plug. In the second location, the spray plumes were targeted towards the piston top in a wall-guided (WG) configuration so as to minimize the impingement of fuel on the liner.

Heterogeneous physical systems can often be considered as highly complex, consisting of a large number of subsystems and components, along with the associated interactions and hierarchies amongst them. The simulation of a large-scale, complex system can be computationally expensive and the dynamic interactions may be highly nonlinear. One approach to address these challenges is to increase the computing power or resort to a distributed computing environment. An alternative to improve the simulation computational performance and efficiency is to reduce CPU required time through the application of surrogate models. Surrogate modeling techniques for dynamic simulation models can be developed based on Recurrent Neural Networks (RNN).This study will present a method to improve the overall speed of a multi-physics time-domain simulation of a complex naval system using a surrogate modeling technique.

The quantification of aircraft survivability in modern battlefield environments is a complex mathematical problem. In general, consideration must be given to the quantification of aircraft vulnerability to individual weapon systems, single encounter aircraft survivability, and the mathematical mapping of single encounter aircraft survivability into mission attrition. A methodology for quantifying the impacts of electronic warfare (EW) upon aircraft survivability is realized by the General Effectiveness Methodology (GEM) which is based upon a hierarchy of computer models. This paper describes this hierarchy of computer simulation tools which extensively employs probability theory to estimate the various engagement events such as aircraft detection, acquisition, missile launch, missile intercept, and probability of aircraft kill.

The upcoming Bharat Stage VI (BS VI) emission legislation has put enormous pressure on the future of small diesel engines which are widely used in the Indian market. The present work investigates the emission reduction potential of a common rail direct injection single cylinder diesel engine by adopting a holistic approach of lowering the compression ratio, boosting the intake air and down-speeding the engine. Experimental investigations were conducted across the entire operating map of a mass-production, light-duty diesel engine to examine the benefits of the proposed approach and the results are quantified for the modified Indian drive cycle (MIDC). By reducing the compression ratio from 18:1 to 14:1, the oxides of nitrogen (NOx) and soot emissions are reduced by 40% and 75% respectively. However, a significant penalty in fuel economy, unburned hydrocarbon (HC) and carbon monoxide (CO) emissions are observed with the reduced compression ratio.

An integrated approach for modeling the ice accretion and shedding of ice on helicopter rotors is presented. A modular framework is used that includes state of the art computational fluid dynamics, computational structural dynamics, rotor trim, ice accretion, and shedding tools. Results are presented for performance degradation due to icing, collection efficiency, surface temperature and water film properties associated with runback-refreeze phenomena, and shedding. Comparisons with other published simulations and test data are given.

The recent development of electric vehicles creates a new area of interest regarding their potential impacts on natural resource and energy networks. Water consumption is of particular interest, as water scarcity becomes a growing problem in many regions of the world. Water usage can be traced to the production of gasoline, as well as electricity, for regular operation of these vehicles. This paper focuses on the development of a framework to analyze the amount of water consumed in the operation of both conventional and electric vehicles. Using the Systems Modeling Language, a model was developed based on the water consumed directly in energy generation and processing as well as water consumed in obtaining and processing a vehicle's fuels. This model and framework will use the above water consumption breakdown to examine conventional and electric vehicles in metropolitan Atlanta to assess their impacts on that and other urban networks.

Spray processes, such as primary breakup, play an important role for subsequent combustion processes and emissions formation. Accurate modeling of these spray physics is therefore key to ensure faithful representation of both the global and local characteristics of the spray. However, the governing physical mechanisms underlying primary breakup in fuel sprays are still not known. Several theories have been proposed and incorporated into different engineering models for the primary breakup of fuel sprays, with the most widely employed models following an approach based on aerodynamically-induced breakup, or more recently, based on liquid turbulence-induced breakup. However, a complete validation of these breakup models and theories is lacking since no existing measurements have yielded the joint liquid mass and drop size distribution needed to fully define the spray, especially in the near-nozzle region.

System effectiveness has become the prime metric for the evaluation of military aircraft. As such, it is the designer's goal to maximize system effectiveness. Industry documents indicate that all future military aircraft will incorporate signature reduction as an attempt to improve system effectiveness. Today's operating environments demand low observable aircraft which are able to reliably eliminate valuable, time critical targets. Thus, it is desirable to be able to evaluate the signatures of a vehicle, as well as the influence of signatures on the systems effectiveness of a vehicle. Previous studies have shown that shaping of the vehicle is one of the most important contributors to radar cross section and must be considered from the very beginning of the design process. This research strives to meet these needs by developing a parametric geometry radar cross section prediction tool.

Several approaches to robust design have been proposed in the past. Only few acknowledged the paradigm shift from performance based design to design for cost. The incorporation of economics in the design process, however, makes a probabilistic approach to design necessary, due to the inherent ambiguity of assumptions and requirements as well as the operating environment of future aircraft. The approach previously proposed by the authors, linking Response Surface Methodology with Monte Carlo Simulations, has revealed itself to be cumbersome and at times impractical for multi-constraint, multi-objective problems. In addition, prediction accuracy problems were observed for certain scenarios that could not easily be resolved. Hence, this paper proposes an alternate approach to probabilistic design, which is based on a Fast Probability Integration technique.

In early phases of conceptual design stages for developing a new car in the modern automobile industry, the lack of systematic methodology to efficiently converge to an agreement between the aesthetics and aerodynamic performance tremendously increases budget and time. During these procedures, one of the most important tasks is to create geometric information which is versatilely morphable upon the demands of both of stylists and engineers. In this perspective, this paper proposes a Spline-based Modeling Algorithm (SMA) to implement into performing aerodynamic design optimization research based on CFD analysis. Once a 3-perspective schematic of a car is given, SMA regresses the backbone boundary lines by using optimum polynomial interpolation methods with the best goodness of fit, eventually reconstructing the 3D shape by linearly interpolating from the extracted boundaries minimizing loss of important geometric features.

One the most critical barriers to the advancement of Personal Air Vehicles in today's market environment is that the technological capabilities can never seem to outweigh the risks associated with financing such an endeavor. To address such a need, a system dynamics approach with the capability to model the uncertainties in the supply chain is presented in this paper. The overall modeling framework is first presented and the modeling process of the various relevant elements, such as demand prediction and manufacturer analysis, is then described. The aim of this research is ultimately to assess the viability of a next-generation aircraft program beyond the static confines of a net present value approach, through the inclusion of dynamic events and uncertainties that can occur throughout the life-cycle of the aircraft.

A technique is proposed for examining complex behaviors in the “pilot - vehicle - operational conditions” system using an autonomous situational model of flight. The goal is to identify potentially critical flight situations in the system behavior early in the design process. An exhaustive set of flight scenarios can be constructed and modeled on a computer by the designer in accordance with test certification requirements or other inputs. Distinguishing features of the technique include the autonomy of experimentation (the pilot and a flight simulator are not involved) and easy planning and quick modeling of complex multi-factor flight cases. An example of mapping airworthiness requirements into formal scenarios is presented. Simulation results for various flight situations and aircraft types are also demonstrated.

Accurate modeling of the internal flow and spray characteristics in fuel injectors is a critical aspect of direct injection engine design. However, such high-fidelity computational fluid dynamics (CFD) models are often computationally expensive due to the requirement of resolving fine temporal and spatial scales. This paper addresses the computational bottleneck issue by proposing a machine learning-based emulator framework, which learns efficient surrogate models for spatiotemporal flow distributions relevant for static coupling injection maps, namely total void fraction, velocity, and mass, within a design space of interest. Different design points involving variations of needle lift, fuel viscosity, and level of non-condensable gas in the fuel were explored in this study. An interpretable Bayesian learning strategy was employed to understand the effect of the design parameters on the void fraction fields at the exit of the injector orifice.

Road accidents and persons killed in India have been reported to the tune of 4,90,383 and 1,38,258 respectively during 2012. On National Highways (NHs), major share of accidents (about 29%) and number of persons killed (35.3%) are observed out of total accidents. National Highways in India constitute about 2% of total road network (92,851 km) in India, but carries about 40% of traffic. 46% (42,829 km) of NHs in India comprises of two-lane and about 19% (17239 km) of NHs are single or intermediate-lane. Road accidents being multi-disciplinary in nature involves attention of multiple departments such as Highways Authority, Police, Motor Vehicles, Automobile Manufacturers, NGOs, etc. Owing to spurt in growth of motor vehicle population in India, road accidents are not reduced significantly despite improvement in NHs (widening of carriageway and riding quality).

Although the design phase can account for a sizable amount of the resources consumed during the product realization process, the time and costs associated with the design process are often neglected when making design decisions. To investigate this issue, we define a process-centric decision model in which the design-phase consumption of resources, such as time and money, is explicitly modeled. While it is clear that the utility of a design is almost always directly impacted by the monetary costs of the design process, our decision model also accounts for the fact that the profit earned by a product depends strongly on its launch date. The decision model allows us thus to consider the trade-off between the time necessary for analysis and the improvement in product quality that results from the analysis. The decision model is sufficiently generic that almost any set of beliefs about the alternatives or analyses, as well as any utility-based preference structure can be modeled.