Resilience is defined as the ability to adaptively deal with system boundaries in the face of the unexpected and unforeseen (Branlat and Woods in AAAI Fall Sympoisum, 2010. http://www.aaai.org/ocs/index.php/FSS/ FSS10/paper/viewPaper/2238). We hypothesize that drawing upon resilience-related knowledge is a prerequisite for such adaptivity. This paper proposes team reflection (Ellis et al. in Curr Dir Psychol Sci 23(1):67-72, 2014) as a macrocognitive function to make the resilience-related knowledge explicit. This knowledge is implicitly available with individual team members active at the sharp end but is never explicitly shared due to invisibility of goal-relevant constraints. To overcome this invisibility, we suggest an application that makes changes in the current rail sociotechnical system visible in terms of the three system boundaries, a variation of the originally proposed by Rasmussen (Saf Sci 27(2/3):183-213, 1997): safety, performance and workload. This allows a team of rail signallers to analyse movements towards system boundaries and share knowledge on these movements. An observational study at a rail control post was conducted to assess the value of team reflection in making resilience-related knowledge explicit. For this purpose, we developed a first prototype of the application concerning the performance boundary only. Using naturalistic observations of a team during a week, we observed how they reflected at the end of their shift on salient system changes. A global content analysis was used to show the relevance of the content to resilience and to test the increase in the resilience-related knowledge throughout the observation period. A specific case of a human approaching the rail tracks, as a potential suicide, was analysed in detail. The results show the value of team reflection on system movements towards their boundaries, thus making goal-relevant constrained knowledge explicit within the operational rail environment.

OCCUPATIONAL APPLICATIONS This article describes an observational study at a rail control post to measure workload weak resilience signals. A weak resilience signal indicates a possible degradation of a system's resilience, which is defined as the ability of a complex socio-technical system to cope with unexpected and unforeseen disruptions. A method based upon a weak resilience signal framework introduces a new metric, stretch, to measure the signals. Stretch is a subjective or an objective reaction of the system to an external cluster event and is an operationalization of variables in an earlier stress-strain model. The stretch ratio between the subjective and objective stretch are used to identify workload weak resilience signals. Weak resilience signals identified during real-time operation revealed obstacles that influence the resilience state and enabled actions to anticipate and mitigate changes to maintain the resilience of the system. TECHNICAL ABSTRACT Background: Continuous performance improvement of a complex socio-technical system may result in a reduced ability to cope with unexpected and unforeseen disruptions. As with technical and biological systems, these socio-technical systems may become "robust, yet fragile." Resilience engineering examines the ability of a socio-technical system to reorganize and adapt to the unexpected and unforeseen. However, the resilience doctrine is not yet sufficiently well developed for designing and achieving those goals, and metrics are needed to identify resilience change. Purpose: A new approach was explored to identify changes in the resilience of a rail system around the workload boundary to anticipate those changes during normal operations and hence improve the ability to cope with unexpected and unforeseen disruptions. Methods: A weak resilience signal framework was developed with a resilience-state model for a railway system, resulting in a generic, quantifiable, weak resilience signal model. Two workload measurements (i.e., external cognitive task load and integrated workload scale) were combined into a new metric called stretch. Heart rate variability was used for correlation and validation. An observational study was used to measure workload weak resilience signal through workload quantification at an operational rail control post. Results: A theoretical resilience-state model for a railway system was developed and used to generate a generic quantifiable weak resilience signal model, forming a weak resilience signal framework that is the basis for a method to

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The investigation is motivated by the dynamic conflict in an air-to-air combat between two aggressive aircraft, both equipped with medium-range guided missiles. This conflict can be viewed as an interaction of a two-target differential game (between the aircraft) with two independent missile-aircraft pursuit-evasion games.The information structure is, however, rather intricate: though perfect information can be assumed between the two aircraft, the missiles have a limited detection range, beyond which information has to be forwarded by the launching aircraft. Moreover, missile firing is assumed to be non-detectable. Problems of such complexity do not fit in the frame of classical differential game theory. The paper describes the analysis of the conflict by means of an Expert System with a "knowledge base" incorporating differential game solution elements. The system simultaneously evaluates potential success with the respective risks and advises the pilot when to fire his missile and when to start an evasive maneuver.

This paper aims to enhance tangibility of the resilience engineering concept by facilitating understanding and operationalization of weak resilience signals (WRSs) in the rail sector. Within complex socio-technical systems, accidents can be seen as unwanted outcomes emerging from uncontrolled sources of entropy (functional resonance). Various theoretical models exist to determine the variability of system interactions, the resilience state and the organization's intrinsic abilities to reorganize and manage their functioning and adaptive capacity to cope with unexpected and unforeseen disruptions. However, operationalizing and measuring concrete and reliable manifestations of resilience and assessing their impact at a system level have proved to be a challenge. A multimethod, ethnographic observation and resilience questionnaire, were used to determine resilience baseline conditions at an operational rail traffic control post. This paper describes the development, implementation and initial validation of WRSs identified and modeled around a 'performance system boundary.' In addition, a WRS analysis function is introduced to interpret underlying factors of the performance WRSs and serves as a method to reveal potential sources of future resonance that could comprise system resilience. Results indicate that performance WRSs can successfully be implemented to accentuate relative deviations from resilience baseline conditions. A WRS analysis function can help to interpret these divergences and could be used to reveal (creeping) change processes and unnoticed initiating events that facilitate emergence that degrades rail-system resilience. Establishing relevant change signals in advance can contribute to anticipation and awareness, enhance organizational learning and stimulate resilient courses of action and adaptive behavior that ensures rail operation reliability.