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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.

This document has been declared "CANCELLED" as of July 2008 and has been superseded by PRI AC7102/1. By this action, this document will remain listed in the Numerical Section of the Aerospace Standards Index noting that it is superseded by PRI AC7102/1. Cancelled specifications are available from SAE.

This Aerospace Standard (AS) establishes the requirements for suppliers of Nonconventional Machining Services to be accredited by the National Aerospace and Defense Contractors Accreditation Program (NADCAP). NADCAP accreditation is granted in accordance with SAE AS7003 after demonstration of compliance with the requirements herein. The requirements may be supplemented by additional requirements specified by the NADCAP Nonconventional Machining and Surface Enhancement (NMSE) Task Group. Using the corresponding Audit Criteria (PRI AC7116) will ensure that accredited Nonconventional Machining suppliers meet all of the requirements in this standard and all applicable supplementary standards. The purpose of this audit program is to assess a supplier's ability to consistently provide a product or service that conforms to the technical specifications and customer requirements.

This Aerospace Standard (AS) is to be used as a supplement to SAE AS7109. In addition to the requirements contained in AS7109, the requirements contained herein shall apply to suppliers seeking NADCAP Coatings accreditation who are engaged in thermal spray.

Abstract Letter from the Guest Editors

Abstract The objective of this article is to evaluate the effects of different blast protective modules to military vehicle structures and occupants. The dynamic responses of the V-shape integral basic armor, the add-on honeycomb sandwich structure module, and the anti-shock seat-dummy system were simulated and analyzed. The improvements of occupant survivability by different protective modules were compared using occupant injury criteria. The integral armored cab can maintain the integrity of the cab body structure. The add-on honeycomb sandwich armor reduces the peak structural deformation and velocity of the cab floor by 34.9% and 47.4%, respectively, compared with the cab with integral armors only. The integral armored cab with the anti-shock seat or the honeycomb sandwich structures reduces the occupant shock responses below the injury criteria. For different blast threat intensities, the selection of appropriate protective modules can meet protection requirements.

Abstract Threat identification and security analysis have become mandatory steps in the engineering design process of high-assurance systems, where successful cyberattacks can lead to hazardous property damage or loss of lives. This article describes a novel approach to perform security analysis on embedded systems modeled at the architectural level. The tool, called Security Threat Evaluation and Mitigation (STEM), associates threats from the Common Attack Pattern Enumeration and Classification (CAPEC) library with components and connections and suggests potential defense patterns from the National Institute of Standards and Technology (NIST) Special Publication (SP) 800-53 security standard. This article also provides an illustrative example based on a drone package delivery system modeled in AADL.

Abstract Autonomy has the potential to make the most radical impact by significantly reducing the number of soldiers in harm’s way and changing the military paradigm. Benefits of autonomy to improve the Army’s mission capabilities and the rapid evolution of military systems exerts pressure to develop these systems quickly. Since the associated technological development is highly fast paced and stochastic, approaches that develop systems for stochastic future scenarios are required. In this article we present a vision for the autonomous high-mobility military systems for that future. We discuss the ramifications of autonomy in five areas: (1) fleet organization, (2) physical attributes of high-mobility military systems, (3) individual behaviors of autonomous assets, (4) interactions between humans and autonomous systems, and (5) operation and teaming strategies. We present the future vision, implications, requirements, and technological challenges for each of the five areas.

This Aerospace Standard (AS) is to be used as a supplement to SAE AS7109. In addition to the requirements contained in AS7109, the requirements contained herein shall apply to suppliers seeking NADCAP Coatings accreditation who are engaged in stripping of coated material.

The objective of this study was to optimize the occupant restraint systems for a light tactical vehicle in frontal crashes. A combination of sled testing and computational modeling were performed to find the optimal seatbelt and airbag designs for protecting occupants represented by three size of ATDs and two military gear configurations. This study started with 20 sled frontal crash tests to setup the baseline performance of existing seatbelts, which have been presented previously; followed by parametric computational simulations to find the best combinations of seatbelt and airbag designs for different sizes of ATDs and military gear configurations involving both driver and passengers. Then 12 sled tests were conducted with the simulation-recommended restraint designs. The test results were further used to validate the models. Another series of computational simulations and 4 sled tests were performed to fine-tune the optimal restraint design solutions.

Project Oculus is an in-flight deployable mechanical arm/pod system that will accommodate 500 pounds of sensor payload, developed for a C-130 military aircraft. The system is designed for use in counter narco-terrorism and surveillance applications by the Department of Defense and the National Guard [1]. A prototype of the system has been built and is in the testing/analysis phase. The purpose of this study was to analyze the actual stresses and strains in the critical areas found using previous Finite Element (FE) simulations and to ensure that acceptable safety requirements have been met. The system components tested will be redesigned, tested, and reconstructed in the case of unacceptable safety factors or if more reliable methods can be implemented. The system was built to be deployed and retracted in flight, to avoid causing any problems in take off and landing.

In 1996 a series of costly and preventable mishaps in Naval Aviation were determined to be the cause of dysfunctional cultures that existed within the mishap squadrons. Soon after, the Navy implemented a two-part process to root out dysfunctional cultures before they could cause further mishaps. The first step is for the squadron to complete a Climate Survey. The Climate Survey is an indicator of potential problems. The next step is for a trained Senior Naval Aviator to conduct a Culture Assessment of the squadron to accurately define the current culture of safety as well as any dysfunctional subcultures. Over the last five years, the Navy has saved $1.1 billion from the implementation of this program.1

Facial recognition software (FRS) is a form of biometric security that detects a face, analyzes it, converts it to data, and then matches it with images in a database. This technology is currently being used in vehicles for safety and convenience features, such as detecting driver fatigue, ensuring ride share drivers are wearing a face covering, or unlocking the vehicle. Public transportation hubs can also use FRS to identify missing persons, intercept domestic terrorism, deter theft, and achieve other security initiatives. However, biometric data is sensitive and there are numerous remaining questions about how to implement and regulate FRS in a way that maximizes its safety and security potential while simultaneously ensuring individual’s right to privacy, data security, and technology-based equality.

This SAE Aerospace Information Report (AIR) is prepared for stakeholders seeking information about the evolution, integration, and approval of SHM technologies for military aircraft systems. The report provides this information in the form of (a) two military organizations’ perspectives on requirements, and (b) general SHM challenges and industry perspectives. The report only provides information to generate awarness of prespectives for military aircraft and, hence, assists those who are involved in developing SHM systems understanding the broad range of regulations, requirements, and standards published by military organizations that are available in the public domain from the military organizations.

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.

Abstract Fighter pilots must study models of aircraft dynamics before learning complex maneuvers and tactics. Similarly, autonomous fighter aircraft applications may benefit from a model-based learning approach. Instead of using a preexisting physics model of a given aircraft, a machine learning system can learn a predictive model of the aircraft physics from training data. Furthermore, it can model interactions between multiple friendly aircraft, enemy aircraft, and the environment. Such a system can also learn to represent state variables that are not directly observable, as well as dynamics that are not hard coded. Existing model-based methods use a deep neural network that takes observable state information and agent actions as input and provides predictions of future observations as output. The proposed method builds upon this approach by adding a residual feedforward skip connection from some of the inputs to all of the outputs of the deep neural network.

The modeling and simulation pyramid in defense states it clearly: Multi-Level modeling and simulation are required. Models and simulations are often classified by the US Department of Defense into four levels—campaign, mission, engagement, and engineering. Campaign simulation models are applied for evaluation; mission-level simulations to experiment with the integration of several macro agents; engagement simulations in engineered systems development; and engineering-level simulation models with a solid foundation in structural physics and components. Models operating at one level must be able to interact with models at another level. Therefore, the cure (“silver bullet”) is very clear: a comprehensive framework for Multiple Resolution Modeling (MRM) is needed. In this paper, we discuss our research about how to construct MRM environments.

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.