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The aim of this paper is to present a numerical analysis of high-speed flows over a missile geometry. The N1G missile has been selected for our study, which is subjected to a high-speed flow at Mach 4 over a range of Angle of attack (AoA) from 0° to 6°. The analysis has been conducted for a 3-dimensional missile model using ANSYS environment. The study contemplates to provide new insights into the missile aerodynamic performance which includes the coefficient of lift (CL) , coefficient of drag (CD) and coefficient of moment (CM) using computational fluid dynamics (CFD). As there is a lack of availability of data for missile geometry, such as free stream conditions and/or the experimental data for a given Mach number, this paper intends to provide a detailed analysis at Mach 4. As the technology is advancing, there is a need for high-speed weapons (missiles) with a good aerodynamic performance, which intern will benefit in reduction of fuel consumption.

This paper describes an approach to integrating high-fidelity vehicle dynamics with a high-fidelity gaming engine, specifically with respect to terrain. The work is motivated by the experimental need to have both high-fidelity visual content with high-fidelity vehicle dynamics to drive a motion base simulator. To utilize a single source of terrain information, the problem requires the just-in-time sharing of terrain content between the gaming engine and the dynamics model. The solution is implemented as a client-server with the gaming engine acting as a stateless server and the dynamics acting as the client. The client is designed to actively maintain a locally cashed terrain grid around the vehicle and actively refresh it by polling the server in an on-demand mode of operation. The paper discusses the overall architecture, the protocol, the server, and the client designs. A practical implementation is described and shown to effectively function in real-time.

Tanks play a pivotal role in swiftly deploying firepower across dynamic battlefields. The core of tank mobility lies within their powertrains, driven by diesel engines or gas turbines. To better understand the benefits of each power system, this study uses geo-location data from the National Training Center to understand the power and energy requirements from a main battle tank over an 18-day rotation. This paper details the extraction, cleaning, and analysis of the geo-location data to produce a series of representative drive cycles for an NTC rotation. These drive-cycles serve as a basis for evaluating powertrain demands, chiefly focusing on fuel efficiency. Notably, findings reveal that substantial idling periods in tank operations contribute to diesel engines exhibiting notably lower fuel consumption compared to gas turbines. Nonetheless, gas turbines present several merits over diesel engines, notably an enhanced power-to-weight ratio and superior power delivery.

Tradespace exploration (TSE) describes the activity occurring early in the design process through which stakeholders explore a broad solution space in search of more-optimal alternatives. In doing so, these stakeholders attempt to maximize the utility inherent in the chosen solution while understanding the tradeoffs and compromises that may be required to find an acceptable solution. In the field of vehicle design, tradespaces are often comprised of vast amounts of alternatives which increases the complexity of the decision-making process. Additionally, the number of stakeholders has grown, as decision-makers seek to include more variety in both perspectives and expertise. As such, decision-making stakeholders can often find themselves working at odds and attempting to maximize vastly different objectives in the process. One way to rectify these contrasting viewpoints can be to intentionally introduce a group framing prior to the start of decision making.

In alignment with the U.S. Army's Climate Strategy and the broader trend in automotive technology, there is a strategic shift towards electrification and hybridization of the vehicle fleet. While a major goal of this effort is to mitigate the carbon footprint of the U.S. Army's vehicle operations, this transition also presents an opportunity to harness advancements in automotive electrification. Among the key vehicles in focus are tactical wheeled vehicles, which provide military forces with versatile and rugged transportation solutions for various combat scenarios, ensuring mobility, protection, and adaptability on the battlefield. This study investigates the potential of electrified tactical wheeled vehicles by conducting a survey involving a diverse group of vehicle operators across various ranks within the U.S. Army.

In recent years, the increasing complexity of modern aerospace systems has driven the rapid adoption of robust Model-Based Systems Engineering (MBSE). MBSE is a development methodology centered around computational models, which are instrumental in supporting the design and analysis of intricate systems. In this context, the Architecture Analysis and Design Language (AADL) and Systems Modeling Language (SysML) are two prominent modeling languages for specifying and analyzing the structure and behavior of a cyber-physical system. Both languages have their own specific use cases and tool environments and are typically employed to model different aspects of system design. Although multiple software tools are available for transforming models from one language to another, their effectiveness is limited by fundamental differences in the semantics of each language.

To many, a digital twin offers “functionality,” or the ability to virtually rerun events that have happened on the real system and the ability to simulate future performance. However, this requires models based on the physics of the system to be built into the digital twin, links to data from sensors on the real live system, and sophisticated algorithms incorporating artificial intelligence (AI) and machine learning (ML). All of this can be used for integrated vehicle health management (IVHM) decisions, such as determining future failure, root cause analysis, and optimized energy performance. All of these can be used to make decisions to optimize the operation of an aircraft—these may even extend into safety-based decisions.

Materials play a key role in our day to day life and have shaped the industrial revolution to a great extent. Right selection of material for meeting a particular objective is the key to success in today’s world where the cost as well as sustainability of any equipment or a system have assumed greater significance than ever before. In automotive industry, materials have a definitive role as far as the mobility and safety is concerned. Materials that can absorb the required energy or impact can be manufactured through different manufacturing as well as metallurgical processes which involves appropriate heat treatment and bringing correct chemical compositions etc. However, they can also be formed by simpler methods such as combining certain materials together in the form of layered combinations to form light weight composites.

Fuel tank is considered as safety component in the vehicle, and it has to be tested to meet the safety requirements as per AIS 095. Earlier, fuel tanks were manufactured by using Hot dipped cold rolled steel material and the weld zones are applied with Anti-corrosive coating. Few fuel tanks were reported with Corrosion problems. The root cause analysis was carried out considering the raw material, manufacturing process, transpiration, storage and usage. As an improvement, the new fuel tank is designed to eliminate the limitations of the existing fuel tank. 3D modeling was done to check space and mounting requirement in the layout and used for volume calculations. FE analysis was performed to check structural stability. Emphasis given on Interchange-ability to cater the new fuel tanks in place of old as spares requirement. The fuel tank has developed with Alumina steel material.

Fatigue analysis of pistons is reliant on an accurate representation of the high temperatures to which they are exposed. It can be difficult to represent this accurately, because instrumented tests to validate piston thermal models typically include only measurements near the piston crown and there are many unknown backside heat transfer coefficients (HTCs). Previously, a methodology was proposed to aid in the estimation of HTCs for backside convection boundary conditions of a stratified charge compression ignition (SCCI) piston. This methodology relies on Bayesian inference of backside HTC using a co-simulation between computational fluid dynamics (CFD) and finite element analysis (FEA) solvers. Although this methodology primarily utilizes the more computationally efficient FEA model for the iterations in the calibration, this can still be a computationally expensive process.

This work covers the historical development of Built-In-Test (BIT) for fiber optic interconnect links for aerospace applications using Optical Time Domain Reflectometry (OTDR) equipped transceivers. The original failure modes found that installed fiber optic links must be disconnected before diagnosis could begin, often resulting in “no fault found” (NFF) designation. In fact, the observed root cause was that most (85%) of the fiber optic link defects were produced by contamination of the connector end faces. In March of 2006, a fiber optics workshop was held with roughly sixty experts from system and component manufacturers to discuss the difficulties of fiber optic test in aerospace platforms. During this meeting it was hypothesized that Optical Time Domain Reflectometry (OTDR) was feasible using an optical transceiver transmit pulse as a stimulus. The time delay and amplitude of received reflections would correlate with the position and severity of link defects, respectively.

As the complexity of systems expands with increasing emphasis for digital transformation, the aerospace industry is generating big data to meet customer requirements. The ability to that data to solve challenging problems is limited by many factors, including the capabilities of current classical computing systems. Impact of Quantum Computing in Aerospace discusses how quantum computing systems offer (possibly quadratic to exponentially) greater computational power over classical computers. The power of quantum computing is tremendous and has many potential impacts on the aerospace industry; however, there are also many unsettled topics surrounding the future of the technology. Click here to access the full SAE EDGETM Research Report portfolio.

A common scenario in engineering design is the availability of several black-box functions that describe an event with different levels of accuracy and evaluation cost. Solely employing the highest fidelity, often the most expensive, black-box function leads to lengthy and costly design cycles. Multi-fidelity modeling improves the efficiency of the design cycle by combining information from a small set of observations of the high-fidelity function and large sets of observations of the low-fidelity, fast-to-evaluate functions. In the context of Bayesian optimization, the most popular multi-fidelity model is the auto-regressive (AR) model, also known as the co-kriging surrogate. The main building block of the AR model is a weighted sum of two Gaussian processes (GPs). Therefore, the AR model is well suited to exploit information generated by sources that present strong linear correlations.

As powertrain hybridization technologies are becoming popular, their application for heavy-duty military vehicles is drawing attention. An intelligent design and operation of the energy management system (EMS) is important to ensure that hybrid military vehicles can operate efficiently, simultaneously maximize fuel economy and minimize monetary cost, while successfully completing mission tasks. Furthermore, an integrated EMS framework is vital to ensure a functional vehicle power system (VPS) to survive through critical missions in a highly stochastic environment, when needed. This calls for situational awareness and dynamic system reconfiguration capabilities on-board of the military vehicle. This paper presents a new energy management and control (EMC) framework based on holistic situational awareness (SA) and dynamic reconfiguration of the VPS.

Tradespace analysis is used to define the characteristics of the solution space for a vehicle design problem enabling decision-makers (DMs) to evaluate the risk-benefit posture of a vehicle design program. The tradespace itself is defined by a set of functional objectives defined by vehicle simulations and evaluating the performance of individual design solutions that are modeled by a set of input variables. Of special interest are efficient design solutions because their perfomance is Pareto meaning that none of their functional objective values can be improved without decaying the value of another objective. The functional objectives are derived from a combination of simulations to determine vehicle performance metrics and direct calculations using vehicle characteristics. The vehicle characteristics represent vendor specifications of vehicle subsystems representing various technologies.

Armoured engineering vehicles are a class of vehicles that cater to the engineering needs such as repair, recovery, technical maintenance, clearing obstacles etc. in field conditions for Main Battle Tanks (MBTs) during times of combat. In addition to the above needs, such vehicles are also supposed to carry sufficient spares including a spare powerpack that includes an engine cum transmission for MBTs as a piggyback during field replacement. Such requirements entail challenges in the design as locating such a powerpack on the vehicle impose additional structural strengthening and stability concerns during both static and dynamic conditions without obviating the need to carry vehicle spares and weight constraints. This paper tries to address these design challenges through a case study, wherein a cover plate that is supposed to seal the powerpack compartment from dust and water ingress is converted to a cover plate cum loading platform.

Investigating the impact of Gasoline fuel on diesel engine performance and emission is very important for military heavy- duty combat vehicles. Gasoline has great potential as alternative fuel due to rapid depletion of petroleum reserves and stringent emission legislations, under multi fuel strategy program for military heavy- duty combat vehicle. There is a known torque, horsepower and fuel economy penalty associated with the operation of a diesel engine with Gasoline fuel. On the other hand, experimental studies have suggested that Gasoline fuel has the potential for lowering exhaust emissions, especially NOx, CO, CO2, HC and particulate matter as compared to diesel fuel. Recent emission legislations also restrict the total number of nano particles emitted in addition to particulate matter, which has adverse health impact.

The “holy grail” for prognostics and health management (PHM) professionals in the aviation sector is to have integrated vehicle health management (IVHM) systems incorporated into standard aircraft maintenance policies. Such a change from current aerospace industry practices would lend credibility to this field by validating its claims of reducing repair and maintenance costs and, hence, the overall cost of ownership of the asset. Ultimately, more widespread use of advanced PHM techniques will have a positive impact on safety and, for some cases, might even allow aircraft designers to reduce the weight of components because the uncertainty associated with estimating their predicted useful life can be reduced. We will discuss how standard maintenance procedures are developed, who the various stakeholders are, and – based on this understanding - outline how new PHM systems can gain the required approval to be included in these standard practices.

The complete lifecycle of complex systems, such as ground vehicles, consists of multiple phases including design, manufacturing, operation and sustainment (O&S) and finally disposal. For many systems, the majority of the lifecycle costs are incurred during the operation and sustainment phase, specifically in the form of uncertain maintenance costs. Testing and analysis during the design phase, including reliability and supportability analysis, can have a major influence on costs during the O&S phase. However, the cost of the analysis itself must be reconciled with the expected benefits of the reduction in uncertainty. In this paper, we quantify the value of performing the tests and analyses in the design phase by treating it as imperfect information obtained to better estimate uncertain maintenance costs.

Currently, for various military activities such as construction of bridges, digging trenches, construction of roads and clearing the area during landslides, separate unit of bulldozer for dozing operation and loader for loading operation is required. But the need is to develop a single unit which could perform both of these operations efficiently and simultaneously. The paper discusses about the development of dozer bucket mechanism as a single unit to perform dozing and loading operation and connected to the amphibious infantry combat vehicle. To develop the dozer bucket mechanism synthesis of mechanism (Linkages and Boom) has carried out and care has taken to fulfill the above stated functional requirement and satisfy the geometrical constraints. The synthesis of mechanism is done with the help of ‘CATIA’ software packages. The force calculation on various joints at the different position of mechanism has evaluated with the help of ’ADAMS’ software.