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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.

“New Space" is reshaping the economic landscape of the space industry and has far-reaching implications for technological innovation, business models, and market dynamics. This change, aligned with the digitalization in the world economy, has given rise to innovations in the downstream space segment. This “servitization” of the space industry, essentially, has led to the transition from selling products like satellites or spacecraft, to selling the services these products provide. This also connects to applications of various technologies, like cloud computing, artificial intelligence, and virtualization. Redefining Space Commerce: The Move Toward Servitization discusses the advantages of this shift (e.g., cost reduction, increased access to space for smaller organizations and countries), as well as the challenges, such as maintaining safety and security, establishing standardization and regulation, and managing risks.

Lubricating oil consumption (LOC) is a direct source of hydrocarbon and particulate emissions from internal combustion engines. LOC also inhibits the lifetime of exhaust aftertreatment system components, preventing their ability to effectively filter out other harmful emissions. Due to its influence on piston ring- bore conformability, bore distortion is arguably the most critical parameter for engine designers to consider in prevention of LOC. Bore distortion also has a significant influence on the contact forces between the piston ring and cylinder wall, which determine the wear rate of the ring and cylinder wall and can cause durability issues. Two drivers of bore distortion: thermal expansion and head bolt stresses, are routinely considered in conformability and contact analyses. Separately, bore distortion/vibration due to piston impact and combustion/cylinder pressures has been previously analyzed in wet liner engines for coolant cavitation and noise considerations.

With technological breakthroughs in electric land vehicles revolutionizing their respective industry, maintenance, repair, and overhaul (MRO) facilities in aviation are also adopting digital technologies in their practices. But despite this drive towards digitalization, the industry is still dominated by manual labor and subjective assessments. Today, several technologies, processes, and practices are being championed to resolve some of these outstanding challenges. Considering this, it is important to present current perspectives regarding where the technology stands today and how we can evaluate capabilities for autonomous decision support systems that prescribe maintenance activities. Overlooking some of these unsettled domain issues can potentially undermine any benefits in speed, process, and resilience promised by such systems.

The purpose of this paper is to make quantitative analysis on the effect of demand side optimization, especially on the reduction of CO2 emission realized by optimizing charging and discharging schedule of battery electric vehicles (BEVs), or by optimized Vehicle-to-Grid (V2G) operations. BEV optimization model is incorporated into the existing electricity supply-demand model to study how the introduction of BEVs make differences on a power system operation, composition of power generation and CO2 emission on the power supply side. Three cases of BEV operation are studied, 1) dumb charging without optimization, 2) optimization of charging, 3) optimization of charging and discharging with Vehicle-to-Grid operations. Analysis is also made on how de-carbonization of the supply side will make differences by studying the case of 2035 and 2040 in addition to 2030, the target year of Japan’s new national energy plan.

Automated vehicles (AVs)—and the automated driving systems (ADSs) that enable them—are increasing in prevalence but remain far from ubiquitous. Progress has occurred in spurts, followed by lulls, while the motor transportation system learns to design, deploy, and regulate AVs. Automated Vehicles: A Human/Machine Co-learning Experience focuses on how engineers, regulators, and road users are all learning about a technology that has the potential to transform society. Those engaged in the design of ADSs and AVs may find it useful to consider that the spurts and lulls and stakeholder tussles are a normal part of technology transformations; however, this report will provide suggestions for effective stakeholder engagement. Click here to access the full SAE EDGETM Research Report portfolio.

Eigenvalues of a simple rotating flexible disk-shaft system are obtained using different methods. The shaft is supported radially by non-rigid bearings, while the disk is situated at one end of the shaft. Eigenvalues from a finite element and a multi-body dynamic tool are compared against an established analytical formulation. The Campbell diagram based on natural frequencies obtained from the tools differ from the analytical values because of oversimplification in the analytical model. Later, detailed whirl analysis is performed using AVL Excite multi-body tool that includes understanding forward and reverse whirls in absolute and relative coordinate systems and their relationships. Responses to periodic force and base excitations at a constant rotational speed of the shaft are obtained and a modified Campbell diagram based on this is developed. Whirl of the center of the disk is plotted as an orbital or phase plot and its rotational direction noted.

Gear profile deviation is the difference in gear tooth profile from the ideal involute geometry. There are many causes that result in the deviation. Deflection under load, manufacturing, and thermal effects are some of the well-known causes that have been reported to cause deviation of the gear tooth profile. The profile deviation caused by gear tooth profile deformation due to interference-fit assembly has not been discussed previously. Engine timing gear trains, transmission gearboxes, and wind turbine gearboxes are known to use interference-fit to attach the gear to the rotating shaft. This paper discusses the interference-fit joint design and the mechanism of tooth profile deformation due to the interference-fit assembly in gear trains. A new analytical method to calculate the profile slope deviation change due to interference-assembly of parallel axis spur gears is presented.

Three-piece oil control rings (TPOCR) are widely used in the majority of modern gasoline engines and they are critical for lubricant regulation and friction reduction. Despite their omnipresence, the TPOCRs’ motion and sealing mechanisms are not well studied. With stricter emission standards, gasoline engines are required to maintain lower oil consumption limits, since particulate emissions are strongly correlated with lubricant oil emissions. This piqued our interest in building a numerical model coupling TPOCR dynamics and oil transport to explain the physical mechanisms. In this work, a 2D dynamics model of all three pieces of the ring is built as the main frame. Oil transport in different zones are coupled into the dynamics model. Specifically, two mass-conserved fluid sub-models predict the oil movement between rail liner interface and rail groove clearance to capture the potential oil leakage through TPOCR. The model is applied on a 2D laser induced fluorescence (2D-LIF) engine.

Topology of liner finish is critical to the performance of internal combustion engines. Proper liner finish simulation processes lead to efficient engine design and research. Fourier methods have been well studied to numerically generate liner topology. However, three major issues wait to be addressed to make the generation processes feasible and reliable. First, in order to simulate real plateau honed liners, approaches should be developed to calculate accurate liner geometric parameters. These parameters are served as the input of the generation algorithm. Material ratio curve, the common geometry calculation method, should be modified so that accurate root mean square of plateau height distribution could be obtained. Second, the set of geometric parameters used in generating liner finish (ISO 13565-2) is different from the set of parameters used in manufacturing industry (ISO 13565-3). Quantitative relations between these two sets should be studied.

With the recent advancement in sensing and controller technologies architecture design of an autonomous driving system becomes an important issue. Researchers have been developing different sensors and data processing technologies to solve the issues associated with fast processing, diverse weather, reliability, long distance recognition performance, etc. Necessary considerations of diverse traffic situations and safety factors of autonomous driving have also increased the complexity of embedded software as well as architecture of autonomous driving. In these circumstances, there are almost countless numbers of possible architecture designs. However, these design considerations have significant impacts on cost, controllability, and system reliability. Thus, it is crucial for the designers to make a challenging and critical design decision under several uncertainties during the conceptual design phase.

The Department of Defense (DoD) faces a similar challenge to the broader aerospace community in that they must integrate and operate a range of systems developed independently over a long period. It has proved difficult for the DoD to manage this network of systems and they must explore other options for analyzing and managing their systems. This paper explores the application of social network analysis tools and metrics to a network of aerospace systems within the U.S. Air Force. The structure of the network includes over one hundred U.S. Air Force systems including, aircraft, unmanned aerial vehicles, munitions, satellites, and command and control systems. The paper describes two separate networks based on direct connections and shared activities between these systems. For each of these networks measures of centrality, degree, closeness, betweenness, and eigenvector, quantify both the interoperability and versatility of the U.S. Air Force systems.

A new multi-scale curved beam based model was developed for piston-ring designs. This tool is able to characterize the behavior of a ring with any cross section design. This paper describes the conformability and ring static twist calculation. The conformability part model the static behavior of the ring in working engine conditions. The model employs the computation scheme that separates the meshing of the structure and local force generation. Additional to the conventional static ring-bore conformability analysis, the conformability model is designed to examine ring-bore and ring-groove interactions in a running engine under varying driving forces and localized lubrication conditions. We made Improvements on the way to handle the effects of the radial temperature gradient compared to the existing models. Examples are given on the effects of ring rotation on the interaction of the ring and a distorted bore as well as the change of local lubrication conditions.

Reliable means for on-board detection of particulate filter failures or malfunctions are needed to meet diagnostics (OBD) requirements. Detecting these failures, which result in tailpipe particulate matter (PM) emissions exceeding the OBD limit, over all operating conditions is challenging. Current approaches employ differential pressure sensors and downstream PM sensors, in combination with particulate filter and engine-out soot models. These conventional monitors typically operate over narrowly-defined time windows and do not provide a direct measure of the filter’s state of health. In contrast, radio frequency (RF) sensors, which transmit a wireless signal through the filter substrate provide a direct means for interrogating the condition of the filter itself.

A new multi-scale curved beam based model was developed for piston-ring designs. This paper describes the free-shape, force in circular bore and closed shape within a flexible band (ovality) related parts. Knowing any one of these distributions, this model determines the other two. This tool is useful in the sense that the characterization of the ring is carried out by measuring its closed shape within a flexible band which is more accurate than measuring its free shape or force distribution in circular bore. Thus, having a model that takes the closed shape within a flexible band as an input is more convenient and useful based on the experiments carried out to characterize the ring.

The increasing use of diesel and gasoline particulate filters requires advanced on-board diagnostics (OBD) to prevent and detect filter failures and malfunctions. Early detection of upstream (engine-out) malfunctions is paramount to preventing irreversible damage to downstream aftertreatment system components. Such early detection can mitigate the failure of the particulate filter resulting in the escape of emissions exceeding permissible limits and extend the component life. However, despite best efforts at early detection and filter failure prevention, the OBD system must also be able to detect filter failures when they occur. In this study, radio frequency (RF) sensors were used to directly monitor the particulate filter state of health for both gasoline particulate filter (GPF) and diesel particulate filter (DPF) applications.

A new ring pack model has been developed based on the curved beam finite element method. This paper describes the first part of this model: simulating gas pressure in different regions above piston skirt and ring dynamic behavior of two compression rings and a twin-land oil control ring. The model allows separate grid divisions to resolve ring structure dynamics, local force/pressure generation, and gas pressure distribution. Doing so enables the model to capture both global and local processes at their proper length scales. The effects of bore distortion, piston secondary motion, and groove distortion are considered. Gas flows, gas pressure distribution in the ring pack, and ring structural dynamics are coupled with ring-groove and ring-liner interactions, and an implicit scheme is employed to ensure numerical stability. The model is applied to a passenger car engine to demonstrate its ability to predict global and local effects on ring dynamics and oil transport.

This paper presents a study of experimental transfer path contribution with the estimation technique of the projected operational force under CVT clutch lockup operational condition. Since transfer path analysis is conducted with respect to the evaluation location, the forces applied onto the substructures are, therefore, also required to estimate the coherent operational forces. In order to estimate the forces, the coherent inertance matrix, which is the projection of the inertance matrix onto the subspace with respect to the evaluation location, is estimated without measuring it directly. The acceleration responses at the connections of the passive substructure are measured by the excitation at the evaluation location with reciprocity. The proposed technique decomposes the acceleration responses into the output and input element vectors on the subspace. With those vectors, the coherent full inertance matrix considering cross coupling effects is constructed.

The challenge of developing a robust, real-time driver gaze classification system is that it has to handle difficult edge cases that arise in real-world driving conditions: extreme lighting variations, eyeglass reflections, sunglasses and other occlusions. We propose a single-camera end-toend framework for classifying driver gaze into a discrete set of regions. This framework includes data collection, semi-automated annotation, offline classifier training, and an online real-time image processing pipeline that classifies the gaze region of the driver. We evaluate an implementation of each component on various subsets of a large onroad dataset. The key insight of our work is that robust driver gaze classification in real-world conditions is best approached by leveraging the power of supervised learning to generalize over the edge cases present in large annotated on-road datasets.

The combustion process after auto-ignition is investigated. Depending on the non-uniformity of the end gas, auto-ignition could initiate a flame, produce pressure waves that excite the engine structure (acoustic knock), or result in detonation (normal or developing). For the “acoustic knock” mode, a knock intensity (KI) is defined as the pressure oscillation amplitude. The KI values over different cycles under a fixed operating condition are observed to have a log-normal distribution. When the operating condition is changed (over different values of λ, EGR, and spark timing), the mean (μ) of log (KI/GIMEP) decreases linearly with the correlation-based ignition delay calculated using the knock-point end gas condition of the mean cycle. The standard deviation σ of log(KI/GIMEP) is approximately a constant, at 0.63. The values of μ and σ thus allow a statistical description of knock from the deterministic calculation of the ignition delay using the mean cycle properties