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Why a Management Academy? Why should you be interested in this Engineering Management Academy from SAE? The answer to these questions lies in the statistics highlighted by surveys of hiring managers. For example, are you aware that: 28% of internal leadership promotions fail On average, it takes six years before an individual receives any formal training after being promoted to a management position Individual contributors, who are technical experts, are usually natural candidates for  promotions to management positions.

Internal audits are a requirement of the AS9100, AS 13100 and RM 13005 and are intended to verify the compliance and effectiveness of an organization's quality management system. The methods and techniques for performing internal audits have significantly changed in the aviation, space and defense industries, and internal auditors must be knowledgeable of these requirements and the expectations as identified in the standard.

Take notes! Take the wheel! There is no better place to gain an appreciation for vehicle dynamics than from the driver’s seat. Spend three, intense days with a world-renowned vehicle dynamics engineer and SAE Master Instructor, his team of experienced industry engineers, and the BMW-trained professional driving instructors. They will guide you as you work your way through 12 classroom modules learning how and why vehicles go, stop and turn. Each classroom module is immediately followed by an engaging driving exercise on BMW’s private test track.

The cost of this introductory course can be applied to the cost of the full courses: C2215, Safety Management Systems for Design, Manufacturing and Maintenance Providers in Aviation C2216, Safety Risk Management and Safety Assurance for Design, Manufacturing and Maintenance Providers in Aviation Historically, organizations tend to be punitive and focused on who to blame when an unwanted event occurs. Investigations can begin with the intent to blame and discipline which leads to adversarial relationships between management and employees. 

As environmental concerns have taken the spotlight, electrified powertrains are rapidly being integrated into vehicles across various brands, boosting their market share. With the increasing adoption of electric vehicles, market demands are growing, and competition is intensifying. This trend has led to stricter standards for noise and vibration as well. To meet these requirements, it is necessary to not only address the inherent noise and vibration sources in electric powertrains, primarily from motors and gearboxes, but also to analyze the impact of the spline power transmission structure on system vibration and noise. Especially crucial is the consideration of manufacturing discrepancies, such as pitch errors in splines, which various studies have highlighted as contributors to noise and vibration in electric powertrains. This paper focuses on comparing and analyzing the influence of spline pitch errors on two layout configurations of motor and gearbox spline coupling structures.

Electric vehicles offer cleaner transportation with lower emissions, thus their increased popularity. Although, electric powertrains contribute to quieter vehicles, the shift from internal combustion engines to electric powertrains presents new Noise, Vibration, and Harshness challenges. Unlike traditional engines, electric powertrains produce distinctive tonal noise, notably from motor whistles and gear whine. These tonal components have frequency content, sometimes above 10 kHz. Furthermore, the housing of the powertrain is the interface between the excitation from the driveline via the bearings and the radiated noise (NVH). Acoustic features of the radiated noise can be predicted by utilising the transmitted forces from the bearings. Due to tonal components at higher frequencies and dense modal content, full flexible multibody dynamics simulations are computationally expensive.

Launch vehicles are vulnerable to aeroelastic effects due to their lightweight, flexible, and higher aerodynamic loads. Aeroelasticity research has therefore become an inevitable concern in the development of the Reusable Launch Vehicle (RLV). RLV is the space analogy of an aircraft, a unanimous solution to achieve more affordable access to space. The lightweight control surface of the RLV signifies the relevance of the study on control effectiveness. It is the capability of a control surface such as an elevon or rudder to produce aerodynamic forces and moments to change the launch vehicle's orientation and maneuver it along the intended flight path. The static aeroelastic problem determines the efficiency of control, aircraft trim behaviour, static stability, and maneuvering quality in steady flight conditions. In this study, static aeroelastic analysis was performed on a typical RLV using MSC/NASTRAN inbuilt aerodynamics.

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.

Design and Manufacturing of an Inclinometer sensing element for launch vehicle applications Tony M Shaju, Nirmal Krishna, G Nagamalleswara Rao, Pradeep K Scientist/Engineer, ISRO Inertial Systems Unit, Vattiyoorkavu, Trivandrum, India - 695013 Indian Space Research Organisation (ISRO) uses indigenously developed launch vehicles like PSLV, GSLV, LVM3 and SSLV for placing remote sensing and communication satellites along with spacecrafts for other important scientific applications into earth bound orbits. Navigation systems present in the launch vehicle play a pivotal role in achieving the intended orbits for these spacecrafts. During the assembly of these navigation packages on the launch vehicle, it is required to measure the initial tilt of the navigation sensors for any misalignment corrections, which is given as input to the navigation software. A high precision inclinometer is required to measure these tilts with a resolution of 1 arc-second.

Abstract : In any human space flight program, safety of the crew is of utmost priority. In case of exigency during atmospheric flight, the crew is safely and quickly rescued from the launch vehicle using Crew escape system. Crew escape system is a crucial part of the Human Space flight vehicle which carries the crew module away from the ascending launch vehicle by firing its rocket motors (Pitch Motor (PM), Low altitude Escape Motor (LEM) and High altitude Escape Motor (HEM)). The structural loads experienced by the crew escape system during the mission abort are severe as the propulsive forces, aerodynamic forces and inertial forces on the vehicle are significantly high. Since the mission abort can occur at anytime during the ascent phase of the launch vehicle, trajectory profiles are generated for abort at every one second interval of ascent flight time considering several combinations of dispersions on various propulsive parameters of abort motors and aero parameters.

A structural load estimating methodology was developed for the RLV-TD HEX-01 mission, the maiden winged body technology demonstrator vehicle of ISRO. The technique characterizes atmospheric regime of flight from vehicle loads perspective and ensures adequate structural margin considering atmospheric variations and system level perturbations. Primarily the method evaluates time history of station loads considering effects of vehicle dynamics and structural flexibility. Station loads in the primary structure are determined by superposition of quasi-static aerodynamic loads, dynamic inertia loads, control surface loads and propulsion system loads based on actual physics of the system. Spatial aerodynamic distributions at various Mach numbers along the trajectory have been used in the study. Argumentation in aerodynamic loads due to vehicle flexibility is assessed through the use of spatial aerodynamic distributions.

Advanced Air Mobility (AAM) envisions heterogenous airborne entities like crewed and uncrewed passenger and cargo vehicles within, and between urban and rural environment. To achieve this, a paradigm shift to a cooperative operating environment similar to Extensible Traffic Management (xTM) is needed. This requires the blending of Traditional Air Traffic Services (ATS) with the new generation AAM vehicles having their unique flight dynamics and handling characteristics. A hybrid environment needs to be established with enhanced shared situational awareness for all stakeholders, enabling equitable airspace access, minimizing risk, optimized airspace use, and providing flexible and adaptable airspace rules. This paper introduces a novel concept of distributed airspace management which would be apt for all kinds of operational scenarios perceived for AAM. The proposal is centered around the efficiency and safety in air space management being achieved by self-discipline.

The evaluation of aircraft characteristics through flight test maneuvers is fundamental to aviation safety and understanding flight attributes. This research project proposes a comprehensive methodology to detect and analyze aircraft maneuvers using full flight data, combining signal processing and machine learning techniques. Leveraging the Wavelet Transform, we unveil intricate temporal details within flight data, uncovering critical time-frequency insights essential for aviation safety. The integration of Long Short-Term Memory (LSTM) models enhances our ability to capture temporal dependencies, surpassing the capabilities of machine learning in isolation. These extracted maneuvers not only aid in safety but also find practical applications in system identification, air-data calibration, and performance analysis, significantly reducing pre-processing time for analysts.

Launch vehicle structures in course of its flight will be subjected to dynamic forces over a range of frequencies up to 2000 Hz. These loads can be steady, transient or random in nature. The dynamic excitations like aerodynamic gust, motor oscillations and transients, sudden application of control force are capable of exciting the low frequency structural modes and cause significant responses at the interface of launch vehicle and satellite. The satellite interface responses to these low frequency excitations are estimated through Coupled Load Analysis (CLA). The analysis plays a crucial role in mission as the satellite design loads and Sine vibration test levels are defined based on this. The perquisite of CLA is to predict the responses with considerable accuracy so that the design loads are not exceeded in the flight. CLA validation is possible by simulating the flight experienced responses through the analysis.

Industries have been increasingly adopting AI based computer vision models for automated asset defect inspection. A challenging aspect within this domain is the inspection of composite assets consisting of multiple components, each of which is an object of interest for inspection, with its own structural variations, defect types and signatures. Training vision models for such an inspection process involves numerous challenges around data acquisition such as insufficient volume, inconsistent positioning, poor quality and imbalance owing to inadequate image samples of infrequently occurring defects. Approaches to augmenting the dataset through Standard Data Augmentation (SDA) methods (image transformations such as flipping, rotation, contrast adjustment, etc.) have had limited success. When dealing with images of such composite assets, it is challenging to correct the data imbalance at the component level using image transformations as they apply to all the components within an image.

Faults if not detected and processed will create catastrophe in closed loop system for safety critical applications in automotive, space, medical, nuclear, and aerospace domains. In aerospace applications such as stall warning and protection/prevention system (SWPS), algorithms detect stall condition and provide protection by deploying the elevator stick pusher. Failure to detect and prevent stall leads to loss of lives and aircraft. Traditional Functional Hazard and Fault Tree analyses are inadequate to capture all failures due to the complex hardware-software interactions for stall warning and protection system. Hence, an improved methodology for failure detection and identification is proposed. This paper discusses a hybrid formal method and model-based technique using STPA to identify and diagnose faults and provide monitors to process the identified faults to ensure robust design of the indigenous stall warning and protection system (SWPS).

In a typical Launch Vehicle (LV), dynamic responses due to various flight events are estimated through Coupled Load Analysis (CLA) where the launch vehicle is coupled with a spacecraft. A launch vehicle is subjected to various loads during its flight due to engine thrust depletion / shut-off, thrust oscillation, wind and gust, maneuvering loads. In aerospace industry a standard CLA is performed by generating the mathematical model of launch vehicle and coupling it with reduced mathematical model of satellite and applying the boundary conditions. A CLA is a time consuming process as several flight instances and load cases need to be considered along with generation of structural dynamic model at each time instants. For every new mission, the satellites are mission specific whereas the launch vehicle and the loads remain unchanged. To take advantage of this fact, a new method called “Fast CLA through Reanalysis technique” is proposed in the present paper.

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From SAE International, SAE MobilityRxiv is a free online preprint server and sharing service for English-language preprints in the mobility/transportation field