A PV installation framework concerning electricity variable rates

This paper assesses building integrated photovoltaic (BIPV) installation parameters based on the profit generated by a photovoltaic system. It takes into consideration a home building case study and it investigates its monthly energy demand based on a specific location and a typical occupancy. The capability of a photovoltaic (PV) system to generate more profit occurs when solar intensity is maximum while the electric energy price is at its highest rate. The paper traces a framework that encompasses different aspects such as energy demand, energy price, and solar intensity. This framework identifies profit alternatives according to different installation parameters. A tool that predicts a PV installation hourly electric energy production is developed. The profit generated is simulated for home buildings located in Beirut (Lebanon) and Xihua (China), both at 33.8° latitude north. The paper highlights a new approach for BIPV installations, taking into account weather conditions, energy demand, and electric energy utility rates.     

A framework to model and manipulate constraints for over-constrained geographic applications

Geographic applications are often over-constrained because of the stakeholders’ multiple requirements and the various spatial, alphanumeric and temporal constraints to be satisfied. In most cases, solving over-constrained problems is based on the relaxation of some constraints according to values of preferences. This article proposes the modelling and the management of constraints in order to provide a framework to integrate stakeholders in the expression and the relaxation of their constraints. Three families of constraints are defined: static vs. dynamic, intra-entity vs. inter-entities and intra-instance vs. inter-instances. Constraints are modelled from two points of view: system with the complexity in time of the different involved operators and user with stakeholders’ preferences. The methodology of constraints relaxation is based on primitive, complex and derived operations. These operations allow a modification of the constraints in order to provide a relevant solution to a simulation. The developed system was applied to reduce the streaming/floods risks in the territory of Pays de Caux (Seine Maritime, France).     

Controller synthesis with guaranteed closed-loop phase constraints

In this paper, we present an analysis and synthesis approach for guaranteeing that the phase of a single-input, single-output closed-loop transfer function is contained in the interval [−α,α] for a given α>0 at all frequencies. Specifically, we first derive a sufficient condition involving a frequency domain inequality for guaranteeing a given phase constraint. Next, we use the Kalman–Yakubovich–Popov theorem to derive an equivalent time domain condition. In the case where , we show that frequency and time domain sufficient conditions specialize to the positivity theorem. Furthermore, using linear matrix inequalities, we develop a controller synthesis approach for guaranteeing a phase constraint on the closed-loop transfer function. Finally, we extend this synthesis approach to address mixed gain and phase constraints on the closed-loop transfer function.     

Adversarial example detection for DNN models: a review and experimental comparison

Deep learning (DL) has shown great success in many human-related tasks, which has led to its adoption in many computer vision based applications, such as security surveillance systems, autonomous vehicles and healthcare. Such safety-critical applications have to draw their path to success deployment once they have the capability to overcome safety-critical challenges. Among these challenges are the defense against or/and the detection of the adversarial examples (AEs). Adversaries can carefully craft small, often imperceptible, noise called perturbations to be added to the clean image to generate the AE. The aim of AE is to fool the DL model which makes it a potential risk for DL applications. Many test-time evasion attacks and countermeasures, i.e., defense or detection methods, are proposed in the literature. Moreover, few reviews and surveys were published and theoretically showed the taxonomy of the threats and the countermeasure methods with little focus in AE detection methods. In this paper, we focus on image classification task and attempt to provide a survey for detection methods of test-time evasion attacks on neural network classifiers. A detailed discussion for such methods is provided with experimental results for eight state-of-the-art detectors under different scenarios on four datasets. We also provide potential challenges and future perspectives for this research direction.

     

Stability margins of nonlinear optimal regulators with nonquadratic performance criteria involving cross-weighting terms

In this paper we derive guaranteed gain, sector, and disk margins for nonlinear optimal and inverse optimal regulators that minimize a nonlinear-nonquadratic performance criterion involving cross-weighting terms. Specifically, sufficient conditions that guarantee gain, sector, and disk margins are given in terms of the state, control, and cross-weighting nonlinear-nonquadratic weighting functions. The proposed results provide a generalization of the “meaningful” inverse optimal nonlinear regulator stability margins as well as the classical linear-quadratic optimal regulator gain and phase margins.     

Cellular polypropylene‐based piezoelectric films

Cellular polypropylene‐calcium carbonate based piezoelectric films were obtained using biaxial stretching and gas‐mediated inflation followed by a corona discharge treatment using home‐made devices. The obtained results revealed a cellular structure that develops at the interface between the solid particles and the polymer matrix and the final piezoelectric coefficient was found to depend both on the gas pressure profile and on time. The inflation step gives better results when the gas pressure is increased in stepwise manner allowing the gas to adequately intrude the cavities and maintain the required pressure. The overall results are discussed in terms of processing conditions and in terms of the developed microstructure. POLYM. ENG. SCI., 2012. © 2012 Society of Plastics Engineers     

Experimental study on micro manufacturing of carbon nanotube (CNT) plastic composites

In recent years, innovative materials such as carbon nanotube composites are finding growing interest in several industrial sectors, from sports and leisure to electronics, automotive, aircraft, and defence. The reinforcing influence of the carbon nanotube is of prime interest. However, technological issues concerning the production methods and the manufacturing processes of carbon nanotube components limit the industrial application of this innovative and interesting material, especially whether small features are required. For this reason, manufacturing strategy involving new production technologies must be designed and developed. This paper studies the challenges of a manufacturing chain based on two manufacturing processes: injection moulding and micro milling. A case study based on these innovative processes is reported and discussed. The propagation chain effect and the influence of each considered process parameter on cutting force and geometrical accuracy of the features (the key characteristics of the process chain) were assessed by means of statistical analysis of variance (ANOVA). The ANOVA analysis demonstrated that cutting forces in micro milling are mainly influenced by the material and percentage of carbon nanotubes, while the main parameter influencing the geometrical accuracy of micro features is the matrix material.     

Understanding carbonaceous deposit formation resulting from engine oil degradation

The formation processes of carbonaceous deposits in the first piston ring grooves of direct injection diesel engines have been studied. Deposits generated during engine tests were analysed by SEM/EDX, thermogravimetric analysis, pyrolysis/gas chromatography/mass spectrometry, and FT-IR spectroscopy. These analyses showed that the deposits, with a structure of cracked varnishes, mainly resulted from the degradation of lubricants. Their state strongly depends on the severity of the tests, which resulted in the formation of two kinds of deposits, termed as ‘oily’ and ‘dry’, according to their content of volatile organic matters. Then, to better understand the deposit formation process, a thermo-oxidative degradation of the lubricating oil was carried out in a tubular furnace, while varying temperature, duration of the test, and adding metallic elements to simulate the engine wear. The consumption of antioxidant additives and the lubricant carbonization were highlighted. Temperature level was identified as the most influential parameter during the lubricant degradation process. The presence of metallic elements appeared to act as a catalyst by speeding up the degradation when the tests duration was increased.     

Adaptive disturbance rejection control for compartmental systems with application to intraoperative anesthesia influenced by hemorrhage and hemodilution effects

Compartmental system models involve dynamic states whose values are nonnegative. These models are widespread in biological and physiological sciences and play a key role in understanding these processes. In this paper, we develop a direct adaptive disturbance rejection control framework for compartmental dynamical systems with exogenous bounded disturbances. The proposed framework is Lyapunov based and guarantees partial asymptotic stability of the closed‐loop system, that is, asymptotic stability with respect to part of the closed‐loop system states associated with the plant dynamics. The remainder of the states associated with the adaptive controller gains are shown to be Lyapunov stable. In the case of bounded energy ??₂ disturbances, the proposed approach guarantees a nonexpansivity constraint on the closed‐loop input–output map between the plant disturbances and performance variables. Finally, a numerical example involving the infusion of the anesthetic drug propofol for maintaining a desired constant level of depth of anesthesia for surgery in the face of continuing hemorrhage and hemodilution is provided. Copyright © 2008 John Wiley & Sons, Ltd.