Global Seismic Oscillations in Soft Gamma Repeaters

There is evidence that soft gamma repeaters (SGRs) are neutron stars which experience frequent starquakes, possibly driven by an evolving, ultra-strong magnetic field. The empirical power-law distribution of SGR burst energies, analogous to the Gutenberg-Richter law for earthquakes, exhibits a turn-over at high energies consistent with a global limit on the crust fracture size. With such large starquakes occurring, the significant excitation of global seismic oscillations (GSOs) seems likely. Moreover, GSOs may be self-exciting in a stellar crust that is strained by many, randomly-oriented stresses. We explain why low-order toroidal modes, which preserve the shape of the star and have observable frequencies as low as ~ 30 Hz, may be especially susceptible to excitation. We estimate the eigenfrequencies as a function of stellar mass and radius, and their magnetic and rotational shiftings/splittings. We also describes ways in which these modes might be detected and damped. There is marginal evidence for 23 ms oscillations in the hard initial pulse of the 1979 March 5th event. This could be due to the $_3t_0$ mode in a neutron star with B ~ 10^{14} G or less; or it could be the fundamental toroidal mode if the field in the deep crust of SGR 0526-66 is ~ 4 X 10^{15} G, in agreement with other evidence. If confirmed, GSOs would give corroborating evidence for crust-fracturing magnetic fields in SGRs: B >~ 10^{14} G.Comment: 12 pages, AASTeX, no figures. Accepted for Astrophysical Journal Letter

Towards improved organisational decision-making - a method and tool-chain

Modern enterprises are large complex systems operating in an increasingly dynamic environment and are tasked to meet organisational goals by adopting suitable course of actions or means. This calls for deep understanding of the enterprise, the operating environment, and the change drivers reactive as well as proactive. Traditionally, enterprises have been relying on human experts to perform these activities. However, the sole reliance on humans for decision making is increasingly unviable given the large size of modern enterprises, fast dynamics, and the prohibitively high cost of incorrect decisions. To address this challenge, we propose a method that leverages existing enterprise modelling (EM) tools to improve the agility of organisational decision-making as well as reducing the analysis burden on human experts. The proposed method artifact employs a design science research methodology and the method is validated using a realistic industrial case to bring out its strengths as well as limitations

The Giant Flare of 1998 August 27 from SGR 1900+14: II. Radiative Mechanism and Physical Constraints on the Source

(ABBREVIATED) The extraordinary 1998 August 27 giant flare places strong constraints on the physical properties of its source, SGR 1900+14. We make detailed comparisons of the published data with the magnetar model. The giant flare evolved through three stages, whose radiative mechanisms we address in turn. A triggering mechanism is proposed, whereby a helical distortion of the core magnetic field induces large-scale fracturing in the crust and a twisting deformation of the crust and exterior magnetic field. The envelope of the pulsating tail of the August 27 flare can be accurately fit, after ~40 s, by the contracting surface of a relativistically hot, but inhomogeneous, trapped fireball. We quantify the effects of direct neutrino-pair emission, thereby deducing a lower bound ~ 10^{32} G-cm^3 to the magnetic moment of the confining field. The radiative flux during the intermediate ~40 s of the burst appears to exceed the trapped fireball fit. The spectrum and lightcurve of this smooth tail are consistent with heating in an extended pair corona, possibly powered by continuing seismic activity in the star. We consider in detail the critical luminosity, below which a stable balance can be maintained between heating and radiative cooling in a confined, magnetized pair plasma; but above which the confined plasma runs away to local thermodynamic equilibrium. In the later pulsating tail, the best fit temperature equilibrates at a value which agrees well with the regulating effect of photon splitting. The remarkable four-peaked substructure within each 5.16-s pulse provides strong evidence for the presence of higher magnetic multipoles in SGR 1900+14. The corresponding collimation of the X-ray flux is related to radiative transport in a super-QED magnetic field.Comment: 11 July 2001, accepted for publication in the Astrophysical Journa

Towards the essence of specifying sociotechnical digital twins

Digital Twins are now mainstream technology in the engineering domain. Capabilities and underpinning concepts are well understood and augmented by proven theories from the physical sciences. Nonetheless the design of digital twins in engineering still remains essential a craft. As digital twin technology merges with more traditional computational modelling approaches such as that found in simulation, new application domains are emerging and public policy experts see significant potential in DT for understanding their complex system areas. Such domains have a significant sociotechnical component and as such a new type of digital twin is required, together with a means of specifying such a digital twin. This paper proposes a specification language/method for this purpose. Requirements elicitation for this language utilises a tabletop paper template that serves as a boundary object between domain experts and technical experts. The language is conformant with accepted practice in simulation methods and its semantics provides a route to implementation of a digital twin. We argue that the language is a contribution to a breadcrumb trail for future work in this emerging application area for digital twins

A wide-spectrum approach to modelling and analysis of organisation for machine-assisted decision-making

This paper describes a modeling approach that helps to represent necessary aspects of complex socio-technical systems, such as organization, in an integrated form and provides a simulation technique for analyzing these organi-sations. An actor-based language is introduced and compared to a conventional simulation approach (Stock-and-Flow) by simulating aspects of a software ser-vices company

An actor based simulation driven digital twin for analyzing complex business systems

Modern enterprises aim to achieve their business goals while operating in a competitive and dynamic environment. This requires that these enterprises need be efficient, adaptive and amenable for continuous transformation. However, identifying effective control measures, adaptation choices and transformation options for a specific enterprise goal is often both a challenging and expensive task for most of the complex enterprises. The construction of a high-fidelity digital-twin to evaluate the efficacy of a range of control measures, adaptation choices and transformation options is considered to be a cost effective approach for engineering disciplines. This paper presents a novel approach to analogously utilise the concept of digital twin in controlling and adapting large complex business enterprises, and demonstrates its efficacy using a set of adaptation scenarios of a large university

OrgML - a domain specific language for organisational decision-making

Effective decision-making based on precise understanding of an organisation is critical for modern organisations to stay competitive in a dynamic and uncertain business environment. However, the state-of-the-art technologies that are relevant in this context are not adequate to capture and quantitatively analyse complex organisations. This paper discerns the necessary information for an organisational decision-making from management viewpoint, discusses inadequacy of the existing enterprise modelling and specification techniques, proposes a domain specific language to capture the necessary information in machine processable form, and demonstrates how the collected information can be used for a simulation-based evidence-driven organisational decision-making

Actor monitors for adaptive behaviour

This paper describes a structured approach to encoding monitors in an actor language. Within a configuration of actors, each of which publishes a history, a monitor is an independent actor that triggers an action based on patterns occurring in the actor histories. The paper defines a model of monitors using features of an actor language called ESL including time, static types and higher-order functions. An implementation of monitors is evaluated in the context of a simple case study based on competitive bidding

Digital twin as risk-free experimentation aid for techno-socio-economic systems

Environmental uncertainties and hyperconnectivity force techno-socio-economic systems to introspect and adapt to succeed and survive. Current practice is chiefly intuition-driven which is inconsistent with the need for precision and rigor. We propose that this can be addressed through the use of digital twins by combining results from Modelling & Simulation, Artificial Intelligence, and Control Theory to create a risk free ‘in silico’ experimentation aid to help: (i) understand why system is the way it is, (ii) be prepared for possible outlier conditions, and (iii) identify plausible solutions for mitigating the outlier conditions in an evidence-backed manner. We use reinforcement learning to systematically explore the digital twin solution space. Our proposal is significant because it advances the effective use of digital twins to new problem domains that have greater impact potential. Our novel approach contributes a meta model for simulatable digital twin of industry scale techno-socio-economic systems, agent-based implementation of the digital twin, and an architecture that serves as a risk-free experimentation aid to support simulation-based evidence-backed decision-making. We also discuss validation of this approach, associated technology infrastructure, and architecture through a representative sample of industry-scale real-world use cases

Language support for multi agent reinforcement learning

Software Engineering must increasingly address the issues of complexity and uncertainty that arise when systems are to be deployed into a dynamic software ecosystem. There is also interest in using digital twins of systems in order to design, adapt and control them when faced with such issues. The use of multi-agent systems in combination with reinforcement learning is an approach that will allow software to intelligently adapt to respond to changes in the environment. This paper proposes a language extension that encapsulates learning-based agents and system building operations and shows how it is implemented in ESL. The paper includes examples the key features and describes the application of agent-based learning implemented in ESL applied to a real-world supply chain