Raytheon Technologies (Italy)

In this paper, we propose a patch-based technique for robust background initialization that exploits both spatial and temporal consistency of the static background. The proposed technique is able to cope with heavy clutter, i.e, foreground objects that stand still for a considerable portion of time. First, the sequence is subdivided in patches that are clustered along the time-line in order to narrow down the number of background candidates. Then, a tessellation is grown incrementally by selecting at each step the best continuation of the current background. The method rests on sound principles in all its stages and only few, intelligible parameters are needed. Experimental results show that the proposed algorithm is effective and compares favorably with existing techniques.

The problem of maximizing a utility function while limiting the outage probability below an appropriate threshold is investigated. A coded-division multi access wireless network under mixed Nakagami-lognormal fading is considered. Solving such a utility maximization problem is difficult because the problem is non-convex and non-geometric with mixed integer and real decision variables and no explicit functions of the constraints are available. In this paper, three methods for the solution of the utility maximization problem are proposed. By the first method, a simple explicit outage approximation is used and the constraint that rates are integers is relaxed yielding a standard convex programming optimization that can be solved quickly but at the price of a reduced accuracy. The second method uses a more accurate outage approximation, which allows one solving the utility maximization problem by the Lagrange duality for non-convex problems and contraction mapping theory. The third method is a combination of the first and the second one. Numerical results show that the first method performs well for average values of the outage requirements, whereas the second one is always more accurate, but is also more computationally expensive. Finally, the third method gives same accuracy as the second one, but has a lower computational complexity only for a small number of transmitters.

The non-stationary nature of data streams strongly challenges traditional machine learning techniques. Although some solutions have been proposed to extend traditional machine learning techniques for handling data streams, these approaches either require an initial label set or rely on specialized design parameters. The overlap among classes and the labeling of data streams constitute other major challenges for classifying data streams. In this paper, we proposed a clustering-based data stream classification framework to handle non-stationary data streams without utilizing an initial label set. A density-based stream clustering procedure is used to capture novel concepts with a dynamic threshold and an effective active label querying strategy is introduced to continuously learn the new concepts from the data streams. The sub-cluster structure of each cluster is explored to handle the overlap among classes. Experimental results and quantitative comparison studies reveal that the proposed method provides statistically better or comparable performance than the existing methods.

The design of large scale complex systems demands the ability to correctly specify and verify as early as possible in the design cycle the interaction of the different components that ensure that the global level requirements are satisfied. We address this issue using an approach based on the notion of contract. In particular, we propose a graphical and text-based language for requirement definition that allows designers to incrementally and hierarchically construct contract specifications for system components by composing a set of simple and intuitive patterns. The patterns have a formal semantics, and are implemented as monitor components in the Simulink framework for runtime verification. The contracts are simulated together with the components to verify both satisfaction and compatibility. A cruise control case study demonstrates the effectiveness of the approach.

The contract-based paradigm, founded on the use of contracts as formal requirements, allows distributed designers to develop different aspects and components of the overall system in a concurrent but controlled way. In this paper we describe an extension of contract-based design that aims at bridging the gap between requirements, as they are identified in current industrial practice, and contracts. Our contributions can be summarized as follows: (1) the contract formalization is enriched with the concept of precondition for the unification of the two traditional contract operators, namely parallel composition and conjunction; (2) the definition of contract completeness has been formalized based on the concept of precondition in order to avoid vacuous contract implementations; (3) two new operators, extension and override, are introduced to support the formalization of evolving requirements; (4) a methodology has been defined for the formalization of contracts starting from requirements using the precondition, extension, override and completeness concepts and (5) a simulation-based support for the methodology using executable monitors has been described.

The evolution of Electrical and Electronic (E/E) architectures in the automotive industry has been a significant factor in the transformation of vehicles from traditional mechanical systems to sophisticated, software-defined machines. With increasing vehicle connectivity and the growing threats from cyberattacks that could compromise safety and violate user privacy, the incorporation of cybersecurity into the automotive development process is becoming imperative. As vehicles evolve into sophisticated interconnected systems, understanding their vulnerabilities becomes essential to improve cybersecurity. This paper also discusses the role of evolving standards and regulations, such as ISO 26262 and ISO/SAE 21434, in ensuring both the safety and cybersecurity of modern vehicles. This paper offers a comprehensive review of the current challenges in automotive cybersecurity, with a focus on the vulnerabilities of the Controller Area Network (CAN) protocol. Additionally, we explore state-of-the-art countermeasures, focusing on Intrusion Detection Systems (IDSs), which are increasingly leveraging artificial intelligence and machine learning techniques to detect anomalies and prevent attacks in real time. Through an analysis of publicly available CAN datasets, we evaluate the effectiveness of IDS frameworks in mitigating these threats.

This paper presents the hardware development of a 1-kV, 500-A solid state circuit breaker (SSCB) based on the newly proposed T-type Modular Dc Circuit Breaker (T-Breaker) system. The novel T-Breaker is a paradigm shift from traditional solutions in that it integrates fault current management and transient compensation functions in one system. The demonstrated T-Breaker system has a modular structure with two SiC-based half bridge sub-modules on each arm. The prototype has been tested to be 99.58% efficient at 500 A and breaks up to 5 kA of fault current.

Following the seminal work of Nesterov, accelerated optimization methods have been used to powerfully boost the performance of first-order, gradient based parameter estimation in scenarios where second-order optimization strategies are either inapplicable or impractical. Not only does accelerated gradient descent converge considerably faster than traditional gradient descent, but it also performs a more robust local search of the parameter space by initially overshooting and then oscillating back as it settles into a final configuration, thereby selecting only local minimizers with a basis of attraction large enough to contain the initial overshoot. This behavior has made accelerated and stochastic gradient search methods particularly popular within the machine learning community. In their recent PNAS 2016 paper, A Variational Perspective on Accelerated Methods in Optimization, Wibisono, Wilson, and Jordan demonstrate how a broad class of accelerated schemes can be cast in a variational framework formulated around the Bregman divergence, leading to continuum limit ODEs. We show how their formulation may be further extended to infinite dimensional manifolds (starting here with the geometric space of curves and surfaces) by substituting the Bregman divergence with inner products on the tangent space and explicitly introducing a distributed mass model which evolves in conjunction with the object of interest during the optimization process. The coevolving mass model, which is introduced purely for the sake of endowing the optimization with helpful dynamics, also links the resulting class of accelerated PDE based optimization schemes to fluid dynamical formulations of optimal mass transport.

This work presents a modeling and analysis framework for heterogeneous industrial networks architectures, which is based on a tight integration of a network simulator with embedded software, middleware and a real-time operating system. This framework is suitable for modeling and simulating the behavior of typical components involved in factory automation applications (e.g., PLCs, remote controllers, operational screens, etc.) when they are connected through heterogeneous industrial networks. Experiments show that the framework allows to take early architectural decisions by evaluating the expected system performance based on the available models.

The design of large scale complex systems demands the ability to correctly specify and verify as early as possible in the design cycle the interaction of the different components to ensure that the global level requirements are satisfied. We address this issue using an approach based on the notion of contract and simulation-based verification. In particular, we extend traditional contract verification methods to target distributed systems, which require an asynchronous communication paradigm. We use a pattern-based language for requirement definition, from which we generate a set of contract monitors implemented in the Simulink framework to observe the underlying system execution and flag violating behaviors. In the paper, we discuss in particular the aspects related to handling the asynchronous interaction between components and their relation to the contract monitors. An automatic towing system case study demonstrates the approach.

A large contributor to modern turbofan engine noise is broadband fan-stage interaction noise. Previously, a low-order method for predicting the broadband interaction noise downstream of the fan exit guide vane was developed and validated against NASA's experimental results for the scaled fan Source Diagnostic Test (SDT). In this paper, predictions obtained with this low-order method are shown for the newer ACAT1 scaled fan experiment. As with the SDT results, the trend with fan speed is shown to be predicted well. The low-order method is then used to investigate the effect of fan geometry, fan speed, fan mass flow rate and interstage gap on the broadband noise in a fan stage. The strongest influencing parameters will be highlighted.

Transport of vanadium ions (V 2+ plus V 3+ ) and water through Nafion® and the anion exchange membrane Fumasep FAPQ-330 were measured as functions of current density in a triple membrane cell. The amount of vanadium moving through FAPQ was an order of magnitude less than through Nafion® at all current densities. A large amount of water, -1.5 moles per mole of univalent positively charged ions, was transferred through FAPQ in the direction opposite to vanadium and current. Relatively little water moved through Nafion® at the same operating conditions.

Computer-mediated communications (CMC) can be used as a substitute for face-to-face (FtF) meetings but their effectiveness is highly context dependent. This paper describes a theoretical framework and initial experimental design for characterizing a travel replacement threshold. This effort begins with a use case of remote engineering maintenance training, conducted in three conditions: side-by-side (physically proximate), teleconference (using off-the-shelf software), and a custom VR/AR system designed to provide the apprentice with a virtual view of both the instructor’s larger scale lab and smaller scale workbench. The research hypotheses, experimental protocol, and dependent measures are described. The task involves an instructor demonstrating a circuit board troubleshooting task to a remote apprentice. The apprentice then completes the trained task independently, and performance and subject preferences are compared across conditions. The details of this paper, the result of extensive literature review and winnowing of variables, may assist researchers exploring CMC, training, or social communication.

Seeking the largest solution to an expression of the form A x <= B is a common task in several domains of engineering and computer science. This largest solution is commonly called quotient. Across domains, the meanings of the binary operation and the preorder are quite different, yet the syntax for computing the largest solution is remarkably similar. This paper is about finding a common framework to reason about quotients. We only assume we operate on a preorder endowed with an abstract monotonic multiplication and an involution. We provide a condition, called admissibility, which guarantees the existence of the quotient, and which yields its closed form. We call preordered heaps those structures satisfying the admissibility condition. We show that many existing theories in computer science are preordered heaps, and we are thus able to derive a quotient for them, subsuming existing solutions when available in the literature. We introduce the concept of sieved heaps to deal with structures which are given over multiple domains of definition. We show that sieved heaps also have well-defined quotients.

An analytical model for a blocking porous electrode is derived and used to predict how ohmic resistance inside micropores that host catalyst nanoparticles affects impedance. This paper revisits a widely used approach for estimating ionic conductivities of catalyst layers in fuel cells. An interfacial term associated with resistance in micropores is derived and added to the classical expression for the impedance of a blocking porous electrode at low frequency. The revised model predicts a physically realistic rise in the real component of the impedance at low frequency when reasonable pore dimensions and conductivities are used as inputs.

A first-of-its-kind examination of broadband noise associated with a far-term advanced low-emission aerocombustor concept is presented. Because of design trends and expected cycle changes for future aircraft propulsion systems, noise generated by sources in the combustor are expected to become of increasing significance for airport-community noise. The paper assesses the impact on legacy semi-empirical noise-prediction methods from the expected radical departures from current combustor operating conditions and designs, such as fuel/air distribution and flame anchoring techniques. Such methods are essential in system-level noise assessments at the preliminary design stage for advanced air transports to assure that overall environmental goals are met. Detailed unsteady pressure measurements, obtained in a fundamental combustion noise experiment using a combustor rig at relevant pressures and temperatures are analyzed. In addition to an advanced far-term low-emissions concept, a reference configuration with the test section arranged to model a modern combustor sector was also studied. For the test rig in the current-generation configuration, the measured broadband acoustic data are reasonably well described by the acoustic-power scaling laws used in legacy semi-empirical noise-prediction methods. For the future-advanced configuration, the legacy scaling laws, with some notable exceptions, provide correct trends, but with much less accuracy.

View Video Presentation: https://doi.org/10.2514/6.2022-1404.vid This work presents the findings from a wall-resolved large-eddy simulation (WRLES) study of a canonical gas turbine film cooling configuration performed using a high-order spectral element computational fluid dynamics (CFD) solver known as Nek5000. In particular, flow over a flat plate with a single row of 7-7-7 shaped cooling holes (represented by a single hole with periodic boundary conditions in the spanwise direction) was examined. Numerical results for the baseline case comprised of blowing ratio (BR) of 2, density ratio of 1.6, inlet freestream Reynolds number of 6000, and 30° cooling hole orientation relative to the mean flow were compared with available experimental data. Thereafter, simulations for hole angles of 25°, 35°, and 40° were performed (at BR = 2) to analyze the impact of hole orientation on the adiabatic cooling effectiveness profiles; blowing ratio was also varied (keeping the cooling hole angle fixed at 30°) to investigate its impact on adiabatic effectiveness. With respect to cooling hole angle, it was found that the 30° case had the best peak cooling effectiveness, whereas the 25° case exhibited a broader effectiveness profile with a lower peak due to the plenum flow being more aligned with the bulk flow. On the other hand, lower blowing ratio cases showed a wider film cooling effectiveness profile, but lower overall cooling effectiveness downstream of the cooling hole due to the specifics of the chosen configuration.

The literature does not report a complete design methodology for WSN applications integrating all these aspects. The proposed methodology allows programmers to write WSN applications by using the system description language SystemC and the Abstract Middleware Environment (AME) framework for fast sim

View Video Presentation: https://doi.org/10.2514/6.2023-4297.vid Fast prediction of the interaction broadband noise produced in a turbofan fan stage can benefit engine preliminary design. Over the years, multiple low-order methods for determining the unsteady response of the fan exit guide vane (FEGV) and related acoustics have been developed. These methods provide reasonable predictions of the interaction broadband noise when the fan wake flow upstream of the FEGV is known. The wake flow has been obtained previously from experiment, high fidelity computations and Reynolds Averaged Navier Stokes (RANS) simulations. In this paper, a machine learning method for obtaining the desired wake flow parameters is presented. The training database consists of 8 fan geometries that include varying lean and sweep with a total of 545 fan speed and mass flow cases. The database is generated using RANS. The efficacy of machine learning as a surrogate model for the wake is explored. The effect of inaccuracies in the learned wakes on the final acoustic prediction are noted. Noise outcomes due to varying fan lean and sweep are explored.

Active species crossover continues to frustrate durational performance for redox flow batteries (RFBs), requiring thorough evaluation of membrane / separator properties. Characterization workflows typically employ a suite of ex situ experimental techniques, but these approaches do not capture the dynamic conditions (e.g., variable concentrations, alternating polarity) encountered in redox flow cells. Here, we report a facile method for assessing crossover directly in redox flow cells—compositionally unbalanced symmetric cell cycling (CUSCC). Based on conventional symmetric cell cycling, CUSCC imposes a concentration gradient between two chemically similar half-cells, inducing species crossover during galvanostatic cycling, which results in a characteristic “capacity gain” over time. We first develop a zero-dimensional model to describe fundamental processes that underpin the technique and examine the dependence of capacity gain on membrane / separator properties and operating conditions. Subsequently, we perform proof-of-principle experiments using FeCl2 / FeCl3 and Nafion 117 as a representative system and demonstrate results consistent with those predicted from simulations. Finally, we use model fits of the capacity gain data to extract membrane transport parameters, obtaining similar values to those measured from ex situ techniques. Overall, this work describes a promising new approach for characterizing species crossover and expands the RFB testing toolbox.