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This paper presents an experimental study of the influence of muzzle devices over bending vibrations of an automatic rifle barrel. Starting from what is theoretically known, that muzzle devices exert a reaction force over the barrel in the post ejection period, we have used a very performant high speed camera to record and analyse how do a 5.56 mm automatic rifle barrel vibrates in the muzzle section, first without any muzzle device than with three different muzzle devices mounted on the barrel. The compared results show that the influence of muzzle devices can be very important. [ABSTRACT FROM AUTHOR]

Outranking relations such as produced by the Electre I or II or the Tactic methods are based on a concordance and non-discordance principle that leads to declaring that an alternative is 'superior' to another, if the coalition of attributes supporting this proposition is 'sufficiently important' (concordance condition) and if there is no attribute that 'strongly rejects' it (non-discordance condition). Such a way of comparing alternatives is rather natural and does not require a detailed analysis of tradeoffs between the various attributes. However, it is well known that it may produce binary relations that do not possess any remarkable property of transitivity or completeness. The axiomatic foundations of outranking relations have recently received attention. Within a conjoint measurement framework, characterizations of reflexive concordance-discordance relations have been obtained. These relations encompass those generated by the Electre I and II methods, which are non-strict (reflexive) relations. A different characterization has been provided for strict (asymmetric) preference relations such as produced by Tactic. In this paper we briefly review the various kinds of axiomatizations of outranking relations proposed so far in the literature. Then we analyze the relationships between reflexive and asymmetric outranking relations in a conjoint measurement framework, consolidating our previous work. Co-duality plays an essential rôle in our analysis. It allows us to understand the correspondence between the previous characterizations. Making a step further, we provide a common axiomatic characterization for both types of relations. Applying the co-duality operator to concordance-discordance relations also yields a new and interesting type of preference relation that we call concordance relation with bonus. The axiomatic characterization of such relations results directly from co-duality arguments. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we present a general framework for the comparison of intervals when preference relations have to established. The use of intervals in order to take into account imprecision and vagueness in handling preferences is well known in the literature, but a general theory on how such models behave is lacking. In the paper we generalize the concept of interval (allowing the presence of more than two points). We then introduce the structure of the framework based on the concept of relative position and component set. We provide an exhaustive study of 2-point and 3-point intervals comparison and show the way to generalize such results to n-point intervals. [Copyright &y& Elsevier]

In the field of Artificial Intelligence many models for decision making under uncertainty have been proposed that deviate from the traditional models used in Decision Theory, i.e. the Subjective Expected Utility (SEU) model and its many variants. These models aim at obtaining simple decision rules that can be implemented by efficient algorithms while based on inputs that are less rich than what is required in traditional models. One of these models, called the likely dominance (LD) model, consists in declaring that an act is preferred to another as soon as the set of states on which the first act gives a better outcome than the second act is judged more likely than the set of states on which the second act is preferable. The LD model is at much variance with the SEU model. Indeed, it has a definite ordinal flavor and it may lead to preference relations between acts that are not transitive. This paper proposes a general model for decision making under uncertainty tolerating intransitive and/or incomplete preferences that will contain both the SEU and the LD models as particular cases. Within the framework of this general model, we propose a characterization of the preference relations that can be obtained with the LD model. This characterization shows that the main distinctive feature of such relations lies in the very poor relation comparing preference differences that they induce on the set of outcomes. [ABSTRACT FROM AUTHOR]

Abstract: Consider a horizontal line in the plane and let be a collection of n circles, possibly of different sizes all tangent to the line on the same side. We define the tangent circle graph associated to as the intersection graph of the circles. We also define an irreflexive and asymmetric binary relation P on A; the pair representing two circles of is in P iff the circle associated to a lies to the right of the circle associated to b and does not intersect it. This defines a new nontransitive preference structure that generalizes the semi-order structure. We study its properties and relationships with other well-known order structures, provide a numerical representation and establish a sufficient condition implying that P is transitive. The tangent circle preference structure offers a geometric interpretation of a model of preference relations defined by means of a numerical representation with multiplicative threshold; this representation has appeared in several recently published papers. [Copyright &y& Elsevier]

In many multi-criteria decision-making applications, the preferential information is of an ordinal nature and appropriate aggregation procedures should be used. In this paper, we build a common axiomatic framework to characterize the “Minimum” procedure as well as two of its refinements, the “DiscriMin” and the “LexiMin”. In practical situations, this axiomatic framework could help to select the best-suited procedure. [Copyright &y& Elsevier]

Peter P. Wakker has forcefully shown the importance for decision theory of a condition that he called “Cardinal Coordinate Independence” (CCI). Indeed, when the outcome space is rich, he proved that, for continuous weak orders, this condition fully characterizes the Subjective Expected Utility (SEU) model with a finite number of states. He has furthermore explored in depth how this condition can be weakened in order to arrive at characterizations of Choquet Expected Utility and Cumulative Prospect Theory. This note studies the consequences of this condition in the absence of any transitivity assumption. Complete preference relations satisfying Cardinal Coordinate Independence are shown to be already rather well-behaved. Under a suitable necessary order denseness assumption, they may always be represented using a simple numerical model. [Copyright &y& Elsevier]

Multiple criteria sorting methods assign objects into ordered categories while objects are characterized by a vector of n attributes values. Categories are ordered, and the assignment of the object is monotonic w.r.t. to some underlying order on the attributes scales (criteria). Our goal is to offer a survey of the literature on multiple criteria sorting methods, since the origins, in the 1980's, focusing on the underlying models. In the first part of the paper, we start by recalling two main models, one based on additive value functions (UTADIS) and the other one an outranking relation (Electre Tri). Then we draw a (structured) picture of multiple criteria sorting models and the methods designed for eliciting their parameters or learning them based on assignment examples. In a second part of the paper, we attempt to provide a theoretical view of the field and position some existing models within it. We then discuss issues related to imperfect or insufficient information. [ABSTRACT FROM AUTHOR]

We axiomatically characterize the χ 2 dissimilarity measure. To this end, we solve a new generalization of a functional equation discussed in Aczel (Lectures on functional equations and their applications. Academic Press, 1966). [ABSTRACT FROM AUTHOR]

The development of a dynamic calibration standard for high-amplitude pressure piezoelectric transducers implies the implementation of a system which can provide reference pressure values with known characteristics and uncertainty. The reference pressure must be issued by a sensor, as a part of a measuring chain, with a guaranteed traceability to an international standard. However, this operation has not been completely addressed yet until today and is still calling further investigations. In this paper, we introduce an experimental study carried out in order to contribute to current efforts for the establishment of a reference dynamic calibration method. A suitable practical calibration method based on the calculation of the reference pressure by measurement of the displacement of the piston in contact with an oil-filled cylindrical chamber is presented. This measurement was achieved thanks to a high speed camera and an accelerometer. Both measurements are then compared. In the first way, pressure was generated by impacting the piston with a free falling weight and, in the second way, with strikers of known weights and accelerated to the impact velocities with an air gun. The aim of the experimental setup is to work out a system which may generate known hydraulic pressure pulses with high-accuracy and known uncertainty. Moreover, physical models were also introduced to consolidate the experimental study. The change of striker's velocities and masses allows tuning the reference pressure pulses with different shapes and, therefore, permits to sweep a wide range of magnitudes and frequencies. [ABSTRACT FROM AUTHOR]

In this paper, several clustering algorithms are investigated in order to group together wind parks with close statistical behavior. Here, the proposed approach is practically founded on a fast incremental algorithm validated by a normalized principal component analysis combined with a k-means process. Both methods are practically based on the definition of a Pearson correlation coefficient. The advantage of such a clustering methodology is mainly perceptible in large-scale electrical systems with increased wind penetration. Indeed, it allows to group together highly correlated wind parks into the same cluster and to integrate them in a realistic way into a nonsequential Monte Carlo adequacy evaluation process. Here, the implemented clustering methodology is applied to 94 wind sites located in Occidental Europe. Then, in order to point out the efficiency of this clustering methodology that is afterwards combined with an original wind speed sampling process, an adequacy study is applied to the Roy Billinton Test System in the particular case of two wind clusters. [ABSTRACT FROM PUBLISHER]

• Multiple impacts with impact rates synchronized with the resonant frequencies of the target material may have a devastating effect on the target. • The triple impact finite element simulations present stronger interactions between on-axis impacts compared to off-axis impacts, indicating increased penetrability when the impact position of the projectiles is aligned with one of the two main axes of the material symmetry. • The results show a gradual increase of the energy absorbing capacity of the aramid fabric with increasing spacing between the impact points. Protection against fragment impacts is a critical concern across various applications. Conventional standardised methods use single-impact tests as a simplified approach for evaluating material resistance against impacting fragments. An alternative, near simultaneous triple impact test was implemented for testing protective equipment and materials against fragmentation, effectively simulating the impact of a dense cluster of fragments. Aramid fabrics, the most common protective measure against fragments, exhibit up to 13 % reduced ballistic resistance under triple impacts opposed to single impact tests signifying the importance of a multi-hit test method when evaluating protection against fragments. In this article, a finite element model is developed to conduct a detailed analysis of the dynamic interactions within a triple impact test. This analysis decouples and isolates the various contributing factors, including: the impacting velocity, the dispersion between impacts, the impact positions with respect to the main axes of material symmetry and the time intervals between the impacting projectiles. The model describes 15 layers of aramid fabric, in a detailed discrete mesoscale format, subjected to single, dual and triple impacting 1.102 g Fragment Simulating Projectiles (FSP) in different configurations using the finite element package LS-Dyna. As anticipated, penetrability increases when the distance between two impacting projectiles decreases. Additionally, on-axis impacts are more likely to result in perforation due to increased stress wave destructive–constructive interferences. Furthermore, the time interval between impacts is found to play a major role on the target's eventual ballistic performance. The oscillating phase caused by the excitation from the preceding impacting projectile, can amplify or diminish the relative impacting velocity of the subsequent projectile by as much as 40 %, resulting in either an over-perforation with residual velocity 55 % of the initial impacting velocity, or no-perforation with 0 % penetration depth. [ABSTRACT FROM AUTHOR]

• An in house pyrotechnical triple launcher is designed and implemented which can shoot three 1.102 g fragment simulating projectiles (FSP) with each shot. • The setup is used to test aramid dry fabrics against fragmentation. • The results show a drop in the target's ballistic limit of up to 13% against triple impacts compared to single impact tests. • Dynamic interactions of multi-site impacts generate multiple stress wave patterns which superimpose, elevating the stress-strain energy density of the material, decreasing its ballistic performance. The ballistic resistance of protective equipment against fragment impacts, such as those typically generated from explosions, has been a major concern the past 50years. The simplifications required to investigate the material response to multiple fragment impacts were set based on the technological limitations of the past. Still, current standardised ballistic testing methodologies consider the interactions between multiple impacting fragments negligible, simulating the multiple impulsive loads with single impact tests. This paper challenges this assumption, introducing the parameters of spacing, formation and timing between multiple impacts in a laboratory test method. An in house pyrotechnical triple launcher is designed and implemented which can shoot three 1.102 g Fragment Simulating Projectiles (FSP) with each shot. An add-on dispersion unit allows for adjusting the distances between the impact points. The control over the projectile velocities and the dispersion of the three impact points enables the simulation of a dense fragment cluster impact with specific characteristics. The setup is used to test Aramid dry fabrics against fragmentation. In total 53 specimens of 15 layers of Kevlar 29 plain weave fabrics are tested against single and triple impacts with two different levels of projectile dispersion. The results show a drop in the target's ballistic limit of up to 13% against triple impacts compared to single impact tests. The fabric's ballistic performance seems to improve with increasing the distances between the impact points. For every triple impact test, the parameters: impacting velocity, distances between impact points, alignment of impact points with the warp and weft directions and time intervals between impacting projectiles is documented. [ABSTRACT FROM AUTHOR]

Motivated by the elicitation or the learning of certain types of models for classifying objects in ordered categories based on several criteria, we categorize the positive Boolean functions up to 6 variables. We list all inequivalent positive Boolean functions and we determine the smallest degree k of the k -additive capacity that can be used for separating their true points from their false points. 1-additive Boolean functions are the well-studied threshold functions. Each function is described by its set of minimal true points. The latter correspond to the minimal winning coalitions of simple games. They also correspond to the minimal sufficient coalitions in the multiple criteria classification models we are interested in, namely, the MR-Sort and the noncompensatory sorting model. [ABSTRACT FROM AUTHOR]

For many years, ballistic performance evaluation of protection structures makes use of the estimation of the ballistic limit velocity V 50 , the projectile impact velocity at which there is a 50 percent probability of perforation of the assessed structure. In recent years, enhancements to risk assessment required the estimation of the entire curve of the probability of perforation. Extreme values of complete perforation (partial penetration) at low (high) impact velocity are rare events of the studied system with binary response experiments. Existing methods have comparable accuracy in estimating the V 50 velocity, and use the normality assumption to estimate any percentile of interest V x . This contribution proposes to model the projectile evolution into the target as a diffusion process using the Brownian motion process. A Chi-square and Kolmogorov–Smirnov goodness of fit test is applied to estimate the drift and diffusion coefficients of the developed stochastic differential equation based on the Monte Carlo simulated sample and the experimental one. Under the assumption of constant drift and diffusion coefficients, the estimated value of the projectile deceleration matches its analytically computed value depending on the system parameters and configuration. The established model presents a comparable predictive ability, as existing methods, of the V 50 with the advantage of defining a bounded velocity interval in which the perforation probability varies from zero to one in accordance with the physical behavior of the system. Furthermore, the fitted model provides the probability perforation of the structure at any impact velocity with an estimate of its variability. [ABSTRACT FROM AUTHOR]

Background and objective The principal challenges in the field of anesthesia and intensive care consist of reducing both anesthetic risks and mortality rate. The ASA score plays an important role in patients' preanesthetic evaluation. In this paper, we propose a methodology to derive simple rules which classify patients in a category of the ASA scale on the basis of their medical characteristics. Methods This diagnosis system is based on MR-Sort, a multiple criteria decision analysis model. The proposed method intends to support two steps in this process. The first is the assignment of an ASA score to the patient; the second concerns the decision to accept—or not—the patient for surgery. Results In order to learn the model parameters and assess its effectiveness, we use a database containing the parameters of 898 patients who underwent preanesthesia evaluation. The accuracy of the learned models for predicting the ASA score and the decision of accepting the patient for surgery is assessed and proves to be better than that of other machine learning methods. Furthermore, simple decision rules can be explicitly derived from the learned model. These are easily interpretable by doctors, and their consistency with medical knowledge can be checked. Conclusions The proposed model for assessing the ASA score produces accurate predictions on the basis of the (limited) set of patient attributes in the database available for the tests. Moreover, the learned MR-Sort model allows for easy interpretation by providing human-readable classification rules. [ABSTRACT FROM AUTHOR]